COMMISSION STAFF WORKING DOCUMENT Accompanying the document COMMUNICATION FROM THE COMMISSION Sixth report on economic, social and territorial cohesion: Investing in Europe's Future
Date: 2014-07-23
Institutions: European Commission
Subjects: EU investment, economic convergence, economic growth, job creation













EUR-Lex - 52014SC0242 - EN











|



52014SC0242

COMMISSION STAFF WORKING DOCUMENT Accompanying the document COMMUNICATION FROM THE COMMISSION Sixth report on economic, social and territorial cohesion: Investing in Europe's Future /* SWD/2014/0242 final */









TABLE OF CONTENTS
Executive Summary................................................................................................. i
Chapter 1: Smart Growth..................................................................................... 1
1..... Introduction...................................................................................................... 1
2..... The crisis suspended the reduction in regional disparities 1
Box on regional economic disparities in the world.......................................... 10
Box on Turkey................................................................................................. 11
Box on Western Balkan................................................................................... 11
3..... Central and eastern Member States maintain a strong industrial sector,
but their agriculture needs to continue to modernise      12
4..... Construction and industry most hit by the crisis................... 14
5..... The crisis led to employment losses, but also some productivity gains................................................................................................................................... 17
6..... Growth in metropolitan regions more prone to booms and Busts than in
rural regions.................................................................................................. 20
6.1.     Capital metropolitan
regions performed well until the crisis led to above average employment losses................................................................................................................ 20
6.2.     GDP growth in rural
regions was lower prior to the crisis, but proved more resilient during the
crisis years........................................................................................................ 24
Box on Commuting and functional geographies............................................. 25
Box on new degree of urbanisation and urban-rural
typology........................ 29
Box on EU-OECD city and commuting zone definition and
metropolitan regions        29
7..... Start-ups rates and Entrepreneurship rely on individual initiative and
the right institutional environment............................................... 31
8..... Innovation remains spatially concentrated............................ 37
8.1.     R&D and the 2020
target................................................................................ 38
Box on Competitiveness and
Innovation Framework Programme.................. 42
Box on Research Framework Programmes...................................................... 43
8.2.     Patenting in the EU
and the USA................................................................... 44
9..... Tertiary educational attainment is increasing, but large disparities
persist................................................................................................................... 48
10... Gaps in the digital and transport networks are being filled, but more
remains to be done........................................................................................ 52
10.1.   Digital networks are
spreading, but unevenly................................................. 52
Box on the digital agenda................................................................................ 53
10.2.   Road network in
central and eastern member states still considerably less developed    54
Box: Common transport policy contributes to cohesion and
regional development, by improving accessibility........................................................................................ 58
10.3.   Low speeds and low
frequencies of trains in central and eastern member states limit their appeal
compared to the car......................................................................................... 58
11... Trade and foreign direct investment stimulate growth in the EU-12       63
12... Regional competitiveness produces limited regional spill-overs in EU‑13................................................................................................................................... 66
13... Conclusion........................................................................................................ 69
Chapter 2: Inclusive growth........................................................................... 72
1..... Introduction.................................................................................................... 72
2..... Crisis wipes out most employment gains since 2000................... 72
2.1.     Employment rates
declined rapidly in the regions most affected the crisis.... 73
2.2.     Unemployment highest
in the EU in over a decade........................................ 76
2.3.     Women have far higher
unemployment rates in southern EU regions............. 79
2.4.     Reduction in
early-school leavers is on track................................................... 82
2.5.     Lifelong learning is
stagnating......................................................................... 84
2.6.     Adult proficiency in
literacy and numeracy needs to be increased in several EU Member States
according to OECD PIAAC........................................................................... 86
3..... Poverty and exclusion increase due to the crisis.................. 87
Box: What does it mean to be ‘at-risk of poverty or
social exclusion’ (AROPE)?          88
3.1.     Severe material
deprivation is highest in the towns, suburbs and rural areas of less developed
Member States................................................................................................. 88
3.2.     Very low work
intensity in more developed MS is concentrated in cities...... 90
3.3.     Higher urban risk of
poverty in more developed MS and a higher risk in towns, suburbs and rural areas
in less developed MS.............................................................................. 91
3.4.     Cities in less
developed Member States are close to the 2020 targets, while cities in more
developed Member States lag behind.............................................................. 95
Box on Social inclusion and social protection policies.................................... 97
3.5.     Quality of life in
European cities varies........................................................... 97
3.6.     Crime rates are higher
in urban regions, border regions and tourism destinations           101
4..... movement of people within and between Member States is spurred by
disparities in employment, wages and health.......................... 103
4.1.     The EU is highly
urbanised and is still urbanising but only slowly............... 103
4.2.     Net migration is the
main source of population growth in the 2000s............ 106
4.3.     More foreign-born
workers have joined the labour market with varying success........... 113
4.4.     Life expectancy is
high, but regional disparities persist................................ 116
4.5.     Human development is
improving in Central and Eastern Member States, but the crisis reduced it in Spain, Greece and Ireland......................................................................... 119
5..... Conclusion...................................................................................................... 121
Chapter 3: Sustainable growth................................................................... 123
1..... Introduction.................................................................................................. 123
2..... The EU needs to mitigate and adapt to Climate change...... 124
2.1.     The EU needs to reduce
its greenhouse gas emissions to reach the 2020 targets 126
2.2.     The EU needs to
increase the use of renewable energy to reach the 2020 targets           129
2.3.     EU needs to adapt to
more frequent and disastrous natural hazards............ 133
3..... Shifting to more sustainable transport can increase energy efficiency and
improve air quality......................................................................... 135
3.1.     Improving
accessibility and energy efficiency.............................................. 136
3.2.     Large cities provide
better access to public transport.................................... 140
3.3.     Congestion is high in
several of the large EU cities...................................... 143
3.4.     Air quality can still
be improved in many places in the EU........................... 144
4..... Making cities more attractive can boost EU Resource Efficiency            147
4.1.     Cities use land more
efficiently..................................................................... 147
4.2.     National and local
policies can shape the location and land use intensity of new developments by
promoting more compact cities...................................................................... 156
5..... Improving Eco-systems and reducing environmental impacts can make the EU
more efficient and a better place to live.................... 157
5.1.     Preserving water
quality and protecting species and habitats....................... 157
5.2.     The treatment of urban
wastewater is necessary for ensuring high quality of water        160
5.3.     Solid waste management
improving but there is still a long way to go in many EU regions       163
5.4.     Sound ecosystems offer
many vital services................................................. 164
5.4.1.       Air quality is still too low in many EU cities................................... 168
5.4.2.       Floodplains can regulate water flows and improve quality efficiently 170
6..... Conclusion...................................................................................................... 173
Chapter 4: Public investment, growth and the crisis.................... 174
1..... Introduction.................................................................................................. 174
2..... the share of growth enhancing spending in public expenditure has
decreased......................................................................................................... 174
2.1.     The crisis pushed up
government deficits...................................................... 174
2.2.     Public investment
supports economic growth............................................... 178
Box: The economic literature on the effect of government
expenditure on growth        179
2.3.     Public expenditure
increased, but now come down...................................... 181
2.4.     Public investment
increased and then dropped............................................. 182
3..... Regional and local authorities play a key role in public expenditure and
investment............................................................................................. 183
3.1.     Regional and local
authorities are responsible for a large share of public expenditure    183
3.2.     Regional and local
authorities manage the majority of public investments... 188
3.3.     The crisis ended a
period of sustained growth of public expenditure by regional and local
authorities...................................................................................................... 189
3.4.     Investing during times
of crisis: direct financing and regional and local investment       192
3.5.     Revenue at
sub-national level relies primarily on transfers............................ 193
3.6.     Public deficit and
public debt of sub-national governments......................... 196
4..... Contribution of cohesion policy to public investment in the Member States................................................................................................................... 199
5..... Investment, state Aids, and EIB Loans............................................. 201
5.1.     Competition policy........................................................................................ 201
5.2.     European Investment
Bank........................................................................... 204
6..... Conclusion...................................................................................................... 206
Chapter 5:  The importance of good governance for
economic and social development........................................................................................................... 207
1..... Why should the EU focus on good governance?..................... 207
2..... Doing business is easier in the North of the EU........................ 209
Box Ease of doing business varies within a country..................................... 210
Box on E-Government and public e-Tendering can improve
the ease of doing business and reduce costs................................................................................................. 212
3..... Most Europeans think corruption is wide spread and a major problem 213
Box: Ways of tackling corruption.................................................................. 217
4..... Governance indicators vary between and within EU Member States      218
4.1.     Some regions have a
far higher (or lower) quality of government................. 219
Box How does European quality of Government index
constructed?.......... 220
4.2.     The authority of EU
regions is growing........................................................ 222
5..... Poor Governance limits the impact of Cohesion Policy..... 226
5.1.     Poor governance can
slow down investment, leading to funding losses....... 226
5.2.     Poor governance can
reduce the leverage effect of Cohesion Policy............ 228
6..... Conclusion...................................................................................................... 230
Chapter 6: The evolution of Cohesion Policy..................................... 231
1..... Introduction.................................................................................................. 231
2..... As the funding grew, the geography became simpler.......... 232
2.1.     Cohesion Policy
expenditure increased as a share of GNI............................ 232
2.1.1.       Cohesion Policy in the 1990s........................................................... 232
2.1.2.       Cohesion Policy since 2000............................................................. 233
2.2.     The geography of the
policy became simpler between 1989 and 2013......... 235
Box on Macro-regional cooperation.............................................................. 240
Box on Territorial Cooperation programmes started in 1989
with INTERREG 241
2.3.     Funding remains
concentrated on the less developed regions....................... 242
Box: Allocations and payments..................................................................... 243
2.4.     The European
Structural Investment Funds and Cohesion Policy................ 243
2.4.1.       The Common Agricultural Policy (CAP) and rural development.... 244
2.4.2.       The Common Fisheries Policy and Integrated Maritime Policy...... 246
2.5.     Aid intensities in
less developed regions rose up to 2000-2006 and have since declined            248
Box on Outermost regions............................................................................. 251
3..... How have the goals changed over time?..................................... 251
3.1.     The initial focus was
on training and mobility............................................... 252
3.2.     The 1970s and 1980s
saw structural unemployment and rapid changes in agriculture and manufacturing................................................................................................ 252
3.3.     The countries joining
the EU in the 1980s and 2000s lacked key infrastructure 252
3.4.     Improving transport
and environmental infrastructure.................................. 254
3.5.     The Lisbon and
Gothenburg Agenda............................................................ 255
3.6.     Europe 2020, poverty reduction, climate change mitigation and beyond GDP 255
Box on Committee of the Regions and the territorial
dimension of Europe 2020 and other EU policies............................................................................................. 258
3.7.     Beyond GDP: poverty,
human development and well-being........................ 258
3.8.     What are the goals of
Cohesion Policy?........................................................ 259
Box on Territorial Cohesion and the Lisbon Treaty of 2007......................... 261
4..... the economic rationale underlying the policy has become more integrated....................................................................................................... 262
4.1.     Cohesion Policy has
moved beyond first nature determinants of growth..... 263
4.2.     Cohesion Policy can
boost growth through investment in second nature determinants of growth....................................................................................................................... 264
4.3.     Cohesion Policy
supports market integration and can help less developed regions grow faster  266
5..... The division of funding between policy areas has evolved as the goals of
the policy have changed................................................................. 267
Box on Financial instruments in 2007-2013.................................................. 269
6..... The impact of the crisis on the 2007-2013 period.......................... 271
6.1.     ESF and the reaction
to the crisis.................................................................. 274
7..... Conclusion...................................................................................................... 275
Chapter 7 Impact of Cohesion Policy....................................................... 276
1..... Introduction.................................................................................................. 276
2..... The results of programmes in 2007-2013........................................... 277
2.1.     The European Regional
Development Fund and Cohesion Fund................. 277
2.1.1.       Gross jobs directly created.............................................................. 277
2.1.2.       Enterprise support............................................................................ 277
Box - Examples of enterprise support schemes............................................. 278
2.1.3.       Support for RTDI............................................................................ 278
2.1.4.       ICT infrastructure............................................................................ 279
2.1.5.       Transport.......................................................................................... 279
2.1.6.       Environmental infrastructure........................................................... 281
2.1.7.       Renewable energy and increased energy efficiency........................ 282
2.1.8.       Tourism, cultural activities, social infrastructure, land reclamation and
urban renewal 282
2.2.     The European Social
Fund............................................................................. 284
2.2.1.       Access to employment..................................................................... 284
2.2.2.       Social inclusion policies................................................................... 285
2.2.3.       Support to enhancing human capital................................................ 286
2.2.4.       Improving institutional capacity...................................................... 286
Box on EU value added through networking and the
dissemination of good practice   288
3..... Evaluation Evidence on the impact of Cohesion Policy.... 288
3.1.     The state of play and
the challenges involved for ERDF and Cohesion Fund co-financed programmes.................................................................................................... 288
3.2.     Evidence from
evaluations of ERDF and CF programmes........................... 291
3.2.1.       Enterprise support............................................................................ 292
3.2.2.       Support of RTDI............................................................................. 293
3.2.3.       Investment in transport.................................................................... 295
3.3.     Evidence from
evaluations of ESF programmes........................................... 296
3.3.1.       Enhancing access to employment.................................................... 297
3.3.2.       Equality between women and men.................................................. 297
3.3.3.       Social inclusion - migrants and minorities....................................... 299
4..... The modelled impact of Cohesion Policy 2000-2006 and 2007-2013          300
5..... Conclusion...................................................................................................... 305
Chapter 8: Cohesion Policy in 2014-2020..................................................... 306
1..... KEY ELEMENTS OF THE REFORM.................................................................. 306
1.1.     New geography and
funding......................................................................... 307
Box 1: The Connecting Europe Facility (CEF)............................................. 308
Box : The European Union Solidarity Fund (EUSF).................................... 309
1.2.     Thematic concentration
in support of Europe 2020....................................... 312
1.2.1.       Targeting resources at key areas of growth..................................... 312
1.2.2.       Promoting employment, education and social inclusion.................. 314
1.3.     Strengthening the
effectiveness of investment.............................................. 316
Box : Criteria for fulfilment of ex-ante conditionality
in the area of R&D and innovation        317
1.4.     Achieving and
demonstrating results............................................................ 317
Box : Intervention logic of Cohesion policy in 2014-20 –
Example for supporting the high-tech sector in a more developed region................................................... 318
1.5.     Aligning EU investment
with the European semester................................... 319
1.6.     A strategic approach
to Public Administration reforms................................ 320
1.7.     Sound economic
governance......................................................................... 321
Box - The link between the macroeconomic framework and
the effectiveness of ESI funds     323
Box EU Budget: commitments vs. payments................................................ 325
Box : Gradual application of macroeconomic conditionality
in case of non-compliance under the Excessive Deficit Procedure  (indicated
timing is purely indicative) 327
1.8.     Preserving
growth-enhancing investment...................................................... 328
1.9.     Linking additionality
verification to the stability and convergence programmes........... 329
1.10.   Increasing the role of
financial instruments................................................... 330
1.11.   Reinforcing
cooperation across Europe......................................................... 331
2..... PRELIMINARY ASSESSMENT OF THE PROGRAMME NEGOTIATIONS 2014-20     335
2.1.     Funding priorities in
2014-20........................................................................ 335
2.2.     Aligning investment
with Country Specific Recommendations................... 341
2.3.     Increasing the impact
of investment and delivering results........................... 343
3..... ESTIMATED IMPACT OF COHESION POLICY 2014-2020............................ 345
Box –Constructing the simulations................................................................ 346
3.1.     Estimated impact at
the national level........................................................... 347
3.2.     Estimated impact at
the regional level........................................................... 349
3.2.1.       Investment in infrastructure............................................................. 350
3.2.2.       Investment in human resources........................................................ 353
3.2.3.       Investment in R&D......................................................................... 353
3.2.4.       Combined impact of investment at regional level........................... 355
Map 1 GDP per head (PPS), 2011. 2
Map 2 Growth of GDP per head in real terms,
2001-2008. 4
Map 3 Growth of GDP per head in real terms,
2008-2011. 4
Map 4 NAFTA GDP per head, 2012. 9
Map 5 Russia, India, China and Brazil, GDP per head, 2010. 9
Map 6: Turkey, GVA per head 2010. 11
Map 7 Metropolitan regions by type. 28
Map 8 Urban-rural regional typology. 28
Map 9 REDI combined index. 36
Map 10 REDI individual dimension. 36
Map 11: Total expenditure on R&D, 2011. 39
Map 12 Total expenditure on R&D, distance
to national target, 2011. 39
Map 13 Regional Innovation Scoreboard, 2014. 41
Map 14 Regional innovation growth performance,
2008-2014. 41
Map 15 Patent applications to the EPO,
2008-2009. 46
Map 16 US, patent applications, 2011-2012. 46
Map 17 Population aged 25-64  with tertiary
educational attainment level, 2013. 47
Map 18 Population aged 25-64  with low
educational attainment level, 2013. 47
Map 19 Population aged 30-34 with a tertiary
educational attainment, 2011-13. 51
Map 20 Population aged 30-34 with high
educational attainment 2011-13 Distance to national 2020 target 51
Map 21: Households with a broadband
connection, 2013. 54
Map 22: Travel speed on the core TEN-T road
network, 1955-2030. 56
Map 23 Highest speed on railway network, 1990. 61
Map 24 Highest speed on railway network, 2013. 61
Map 25 Passenger trains on TEN-T railway network, 
2010. 62
Map 26 Access to passenger flights, 2011. 62
Map 27 Employment in foreign firms, 2010. 65
Map 28: Regional Competitiveness index, 2013. 69
Map 29 Employment rate, (ages 20-64), 2013. 74
Map 30 Employment rate, (ages 20-64), 2013 - 
Distance to National 2020 target 74
Map 31 Unemployment rate, 2013. 77
Map 32 Change in unemployment rate, 2008-2013. 77
Map 33 Youth unemployment rate, 2013. 78
Map 34 Population aged 15-24 not in
employment,  education or training, 2013. 78
Map 35 Difference between female and male
unemployment rate, 2013. 80
Map 36 Difference between female and male
employment rate, 20-64, 2013. 80
Map 37 Gender balance of population 50-54 with
tertiary education, 2011-13. 81
Map 38 Gender balance of population 30-34 with
tertiary education, 2011-13. 81
Map 39 Early leavers from education and
training  aged 18-24, average 2011-2013. 83
Map 40: Early school leavers aged 18-24 in
2011-13 -  Distance to national 2020 target 83
Map 41 Low achievers in mathematics, reading
and science. 84
Map 42 Participation of adults aged 25-64 in
education and training, 2013. 85
Map 43 At-risk-of-poverty rates, 2011. 93
Map 44 Population
at-risk-of-poverty-or-social-exclusion, 2012. 94
Map 45 Population
at-risk-of-poverty-or-social-exclusion in 2012, distance to national 2020
target 94
Map 46 Registered thefts of motor vehicles per
capita, 2008-2010. 102
Map 47 Registered domestic burglaries per capita,
2010. 102
Map 48 Population change, 1961-2001. 105
Map 49 Total population change, 2001-2011. 109
Map 50 Natural population growth, 2001-2011. 110
Map 51 Net migration, 2001-2011. 110
Map 52 Regions for cross-border cooperation,
2014-2020. 112
Map 53 EU Life expectancy, 2011. 117
Map 54: USA Life expectancy, 2010. 117
Map 55 Infant mortality, 2012. 118
Map 56 Road fatalities, 2012. 118
Map 57 EU Human development index, 2012. 120
Map 58 Change in the EU Human Development
Index,  2008-2012. 120
Map 59: Potential vulnerability from climate
change. 126
Map 60 Average suitability for photovoltaic
systems. 132
Map 61 Congestion index on the high speed road
network, 2012. 144
Map 62 Annual mean concentrations of PM10,
2011. 146
Map 63 Ozone concentration, 2011. 146
Map 64 Share of Built-up area, 2012. 148
Map 65 Built-up area per head, 2012. 148
Map 66 Change in land use in Vienna, Palermo, Prague and Helsinki, 1950s-2006. 152
Map 67 – Land use changes 2006-2012. 154
Map 68 Ecological status of main water bodies. 158
Map 69 NATURA 2000 areas, 2012. 158
Map 70: Urban wastewater with more stringent
treatment, 2010. 162
Map 71 Urban wastewater not collected, 2010. 162
Map 72: Capacity to deliver ecosystem
services,  TESI index, EU NUTS 2 regions. 167
Map 73: Green infrastructure, EU NUTS 2
regions (% of the surface area covered with green infrastructure) 167
Map 74: Removal capacity in larger urban zones. 169
Map 75 NO2 daily average
concentrations, 2011. 169
Map 76: Nitrogen discharge/retention from Europe's major rivers. 172
Map 77 Regional aid, 2007-2013. 204
Map 78: Corruption Perception Index, 2012. 216
Map 79 European Quality of Government index,
2013. 221
Map 80 Regional self-rule index, 2011. 224
Map 81 Change in regional self-rule index,
1960-2011. 224
Map 82: Cohesion Policy, categories of
regions: 1989-2013. 238
Map 83 Europe 2020 index, 2011 distance to EU
targets. 257
Map 84 Europe 2020 index, 2011 distance to
national targets. 257
Map 85 Structural Funds (ERDS and ESF)
eligibility 2014-2020. 310
Map 86 Cohesion Fund eligibility 2014-2020. 310
Map 87 Investment for growth and jobs goal:
maximum co-financing rate for Structural Funds support, 2014-2020  311
Map 88 Funding for R&D&I,
competitiveness of SMEs  and the low carbon economy, 2014-2020  313
Map 89 Funding for the low-carbon economy,
2014-2020. 313
Map 90 Youth employment initiative, 2014-2020. 315
Map 91 Cross-border cooperation programmes
2014-2020. 333
Map 92: Transnational cooperation programmes
2014-20. 334
Map 93: Impact of interventions in
infrastructure on NUTS 2 regions accessibility, 2030. 351
Map 94: Impact of interventions in
infrastructure on NUTS 2 regions GDP, 2030. 351
Map 95: Short run and long run impact of a
reduction in transport costs in five Polish regions  352
Map 96: Impact of interventions in human
resources on NUTS 2 regions GDP, yearly average 2014-2023  354
Map 97: Impact of interventions in R&D on
NUTS 2 regions GDP, yearly average 2014-2023  354
Map 98: Impact of the 2014-2020 cohesion
policy programmes on NUTS 2 regions GDP, yearly average 2014-2023  357
Map 99: Impact of the 2014-2020 cohesion
policy programmes on NUTS 2 regions GDP in 2030  357
Figure 1: Coefficient of variation (2000 =
100), GDP per head, employment rate, unemployment rate, EU-27 NUTS 2 regions,
2000-2012. 3
Figure 2: Theil index, GDP per head, EU-28
NUTS 2 regions, 2000-2015. 6
Figure 3: GDP per head growth rates of regions
in less developed or moderately developed Member States, 2003-2011. 7
Figure 4: Growth of GDP per head in real
terms, 2001-2015. 8
Figure 5 Industry (excluding construction) in
the EU, 1970-2012. 13
Figure 6 Industry (excluding construction) in
the EU-12, 1995-2012. 14
Figure 7 Agriculture in the EU-12, 1995-2012. 14
Figure 8: Agriculture in the EU, 1970-2012. 14
Figure 9: Larger metropolitan areas are more productive. 22
Figure 10: Population size and productivity by city. 22
Figure 11: Less fragmented metropolitan areas have experienced higher growth. 23
Figure 12: Governance institutions and selected outcomes. 24
Figure 13 GDP per head and per person employed
in the Paris Metropolitan regions, 2010. 27
Figure 14 Birth rates of enterprises, 2010. 32
Figure 15 Death rates of enterprises, 2010. 32
Figure 16 Tertiary educational attainment
country and regional extremes, 2013. 49
Figure 17 Low education rates by country and
regional extremes, 2013. 49
Figure 18: NGA broadband coverage, 2012 (% of
rural and urban population with NGA) 53
Figure 19 - Railway length per capita with
trains operating over 120 km/h, 2013. 60
Figure 20– Change in Railway length per capita
with trains operating over 120 km/h, 1990-2013  60
Figure 21 Trade between EU-12 and EU-27,
2004-2012. 63
Figure 22 FDI in the EU-12, 2005-2012. 64
Figure 23: Weights used in the regional
competitiveness index 2013. 66
Figure 24 - Regional competitiveness index,
2013. 67
Figure 25 Adult literacy proficiency, 2012. 87
Figure 26 Adult numeracy proficiency, 2012. 87
Figure 27 Severe material deprivation by
degree of urbanisation, 2008-2012. 89
Figure 28 Very low work intensity by degree of
urbanisation, 2008-2012. 90
Figure 29 At-risk-of-poverty rate by degree of
urbanisation, 2008-2012. 92
Figure 30 At risk of poverty or exclusion by
degree of urbanisation,  2008-2012 and national 2020 targets  96
Figure 31 Population born outside the EU-27,
2001-2012. 113
Figure 32 Population born in a different EU-27
country per MS, 2001-2012. 114
Figure 33 Employment rate by country of birth,
2013. 115
Figure 34 – Change in greenhouse gas emissions
outside the Emissions Trading Scheme, 2005-2011 and Europe 2020 targets. 128
Figure 35 – Share of renewable energy in gross
final energy consumption, 2006, 2012, target 2020 (% of total gross final
energy consumption) 130
Figure 36 - Modal split of Passenger Transport
on Land by Country - 2011. 137
Figure 37- Modal split Change of
Passenger Transport on Land by Country, 1995 - 2011. 138
Figure 38 Share of passenger travel by mode of
transport in EU Member States, 2011. 139
Figure 39 Share of freight by mode of
transport in EU Member States, 2011. 139
Figure 40 - Access to public transport in
large European cities, 2012. 141
Figure 41 - Access to public transport in
mid-size European cities, 2012. 142
Figure 42. Relationship between population
density and sealed soil per head in larger urban zones, 2006. 149
Figure 43 Population density profile of a
selection of large European capital cities, 2006. 150
Figure 44 Population density profile of a
selection  of mid-sized European capital cities, 2006. 150
Figure 45 – General government balance, EU-27
average,  2000-2013 (% of GDP) 175
Figure 46 – General government balance, Member
States  (ordered by deficit in 2012), 2006, 2009 and 2013 (as % of GDP) 176
Figure 47 – General government expenditure,
revenue (EUR bn, 2005 prices)  and general government balance, EU-27, 2000-2013
(% of EU GDP) 177
Figure 48 – Average annual change in general
government expenditure,  volume, 2000-2009, 2009-2013 (%) 178
Figure 49 – General government expenditure on
growth friendly categories (% of total general government expenditure), 2012. 182
Figure 50 - Public and private fixed
investment, EU-27, 1995-2014  (Gross Fixed Capital Formation as % of GDP) 183
Figure 51 - Sub-national governments
expenditure in general government expenditure, EU-27, 1995 and 2013 (% of
general government expenditure) 184
Figure 52 - Sub-national government
expenditure, 2013 (% of GDP) 184
Figure 53 - Growth Enhancing Expenditure, 2012
(% of national GDP) 187
Figure 54 - Sub-national governments
investment, 2000 and 2013 (% of total public investment) 189
Figure 55 - Average annual change in
sub-national government  expenditure, volume, 2000-2009, 2010-2013 (%) 190
Figure 56 - Sub-national government
investment, EU-27, 1997-2013 (% of GDP) 190
Figure 57 – Average annual change in
sub-national government investment, volume, 2000-2009, 2010-2013 (%) 191
Figure 58 - Sub-national governments'
investment, 1997, 2013 and historical lows (% of national GDP) 192
Figure 59: Sub-national direct financing
capacity and public investment 193
Figure 60 – Annual average change in
sub-national government revenue in real terms, 2000-2009, 2009-2013 (%) 194
Figure 61 - Sources of sub-national government
revenue, 2013 (% of total revenue) 195
Figure 62 – Change in net transfers between
central and State-local Governments,  2009-2013 in real terms, 196
Figure 63 – Sub-national government
expenditure, revenue (EUR bn, 2005 prices) and sub-national governments deficit
(% of EU GDP), EU-27, 2000-2013. 197
Figure 64 - Sub-national governments deficit,
Member States, 2007 and 2013 (% of national GDP) 198
Figure 65 - Consolidated General Government
gross debt, 2013 (% GDP) 199
Figure 66- Contribution of Cohesion Policy
(CP) to public investment in the EU-28 (2007-2013) 200
Figure 67 European Investment Bank loans per
Member State, 2007-2013. 205
Figure 68: WB Doing Business, 2006-2014. 210
Figure 69 e-Government usage by citizens,
2011-2012. 212
Figure 70 Enterprises using the internet in
public e-Tendering, 2012. 212
Figure 71: Corruption is a major problem, 2011. 214
Figure 72 How widespread is corruption in your
country, 2013. 215
Figure 73: World Bank, Government
effectiveness and Rule of Law, 1996-2012. 218
Figure 74 Cohesion Policy funding absorption
and Government effectiveness, 2014. 227
Figure 75: Cohesion policy expenditure in the
EU, 1976-2012. 232
Figure 76: Cohesion Policy expenditure per MS,
1990-1999. 233
Figure 77: Cohesion Policy expenditure per MS,
2000-2006. 234
Figure 78: Cohesion Policy expenditure per MS,
2007-2012. 235
Figure 79: Aid intensity in less developed
regions by Member State, 1989-2006. 249
Figure 80: Aid intensity in less developed
regions by Member State, 2007-2013 and 2014-2020  250
Figure 81: Aid intensities in the outermost
regions, 2007-2020. 251
Figure 82: Unemployment rate, EU-6 EU-27,
1960-2012. 252
Figure 83: GDP per head per enlargement,
1975-2013. 253
Figure 84: Unemployment per EU enlargement,
1973-2013. 254
Figure 85: Share of EU funding reallocated
between policy areas. 272
Figure 86: Reduction in national
cofinancing to end 2013. 273
Figure 87: Funding absorption and project
selection by Member States for the 2007-2013 programming period  274
Figure 88: Estimated impact of Cohesion Policy
2000-2006 on GDP. 301
Figure 89 Estimated impact of Cohesion Policy
2007-2013 on GDP. 302
Figure 90: Principle
of excellence. 321
Figure 91 : Allocation to thematic objectives
(EUR billion at current prices) 336
Figure 92 : Allocations to thematic objectives
(% of total) 336
Figure 93 : Allocation to thematic objective
by Fund (EUR billion at current prices) 337
Figure 94 : Allocations to thematic objectives
by Fund (% of Fund total) 338
Figure 95 : Allocation to thematic objective
by group of countries (% of total) 339
Figure 96 Allocations to thematic objectives
by group of countries (EUR billion at current prices, excluding technical
assistance) 339
Figure 97 : Allocations by thematic objective
2014-20 vs. 2007-13 in the EU-28 (% of total) 340
Figure 98 : Allocations by thematic objective
2014-20 vs. 2007-13 in more developed Member States (% of total) 341
Figure 99 : Allocations by thematic objective
2014-20 vs. 2007-13 in less developed Member States (% of total) 341
Figure 100 : Estimated impact of Cohesion
Policy on GDP. 347
Figure 101: Estimated impact of Cohesion
Policy expenditure on GDP in main beneficiary countries, average 2014-2023. 348
Figure 102 - Cohesion
Policy expenditure and impact, average 2014-2023. 348
Figure 103: Estimated impact of Cohesion Policy expenditure. 349
Table 1: Key indicators for Western Balkan, 2003-2012. 12
Table 2 Change in employment and GVA by sector per group
of member states, 2000-2012  16
Table 3: Decomposing average annual change in GVA per
head per MS, 2001-2008 and 2008-2012  19
Table 4 Change in GDP per head, productivity and
employment per head by type of metropolitan region, 2000-2008 and 2008-2011. 21
Table 5: Real GDP per head, productivity and employment
per head growth by urban-rural typology, 2000-20011  25
Table 6 Total R&D expenditure and the distance to the
2020 target, 2011. 38
Table 7 Population aged 30-34 with a tertiary education,
average 2013. 50
Table 8 Employment rate of those aged 20-64, 2000 - 2013 
and distance to national target 73
Table 9 Unemployment rate by category of region,
2000-2013. 76
Table 10 Early school leavers and distance to national
target, 2008-2013. 82
Table 11 Population change by urban-rural typology,
1961-2011. 104
Table 12 Population by degree of urbanisation, 1961-2011. 106
Table 13 Population change, natural change and net
migration by urban-rural typology, 2001-2011  107
Table 14 Population age structure by urban-rural
typology, 2012. 108
Table 15 - Population change, natural change and net
migration in terrestrial border regions, 2001-2011  111
Table 16 Built-up area per inhabitant, 2012 (in sq km per
million inhabitants) 147
Table 17 - Sub-national governments expenditure by
function, 2013  (% of total Sub-national governments expenditure) 185
Table 18 - Sub-national governments expenditure by
economic sector, 2013 (% of total general government expenditure) 186
Table 19 Starting a business in 2014. 209
Table 20 Estimated direct costs of corruption in public
procurement 216
Table 21 Type of corruption by policy area. 217
Table 22 Dimensions of regional authority (self-rule) 223
Table 23 Population by category of region, 1989-2020 (%) 236
Table 24: Funding for territorial cooperation, 1989-2020. 241
Table 25: Funding distribution between categories of
regions, 1989-2020 (%) 242
Table 26: Annual Aid intensity per category of region,
EUR per head (at 2011 constant prices), 1989-2020  243
Table 27 Allocation per fund (EUR billion, at 2011
prices), 1989-2020. 244
Table 28: Cohesion Policy funding by broad policy area in
EU-15, 1989-2013. 268
Table 29 Cohesion Policy funding by broad policy area in
acceding countries, 2004-2013. 269
Executive
Summary
This report comes out at the start of a new
7-year programming period for Cohesion Policy, when the situation in the EU is dramatically
different from what it was at the start of the previous period in 2007. Then, the
EU was still enjoying a sustained period of economic growth. Income levels were
rising, as were employment rates and public investment, poverty and social
exclusion were diminishing and regional disparities were shrinking. Nevertheless,
despite the positive tendencies, disparities between regions of many different
kinds remained wide. 
The advent of the crisis changed all this. Since
2008, public debt has increased dramatically, income has declined for many
people across the EU, employment rates have fallen in most countries and
unemployment is higher than for over 20 years, while poverty and social exclusion
have tended to become more widespread. At the same time, regional disparities
in employment and unemployment rates have widened as have those in GDP per head
in many countries while in others they have stopped narrowing. These
developments mean that the Europe 2020 employment and poverty targets are now
significantly further away than when they were first set and it will require a
substantial effort over the next 6 years to achieve them in a context of
significant budgetary constraints. 
Chapter 1: In its first stage the crisis
had a big impact on construction and manufacturing. In both, employment fell
markedly, in construction as a result of the collapse of a real estate bubble
in some Member States and a reduction in public investment and manufacturing
because of a decline in global demand, especially for investment goods. More
recently, world markets have expanded and exports have increased giving rise to
some growth of manufacturing. This is particularly important for many of the Central
and Eastern European Member States where manufacturing accounts for a large
share of value-added. 
The territorial impact of the crisis has
been mixed. In most parts of the EU, metropolitan regions have been shown to be
more prone to booms and busts, while overall rural regions have proved more resilient.
In the EU-15, second-tier metropolitan regions performed average, while in the
EU-13, they outperformed the other regions. Rural regions in the EU-15 had a
smaller contraction of GDP than the other regions between 2008 and 2011 due to
higher productivity growth. Also in the EU-13, higher productivity growth meant
that he closed the growth gap with the other regions.
Not all developments, however, have been
unfavourable. Despite the difficult economic context, the proportion of people
with tertiary education has increased over recent years in most countries and
early school leaving rates have declined. As a result, EU targets for both of
these are likely to be reached by 2020 if not earlier. At the same time, R&D
has not declined relative to GDP during the crisis and has even started to increase
slightly in the past year or two, though not by enough to reach the 3% target
set for 2020. Innovation, however, remains highly concentrated in spatial terms
and shows no sign of spreading to lagging regions.
Investment in transport and digital
infrastructure has reduced the deficiencies in these networks in many rural
areas and less developed regions. Access to the internet using the next
generation technology, however, creates new challenges for rural areas where
this technology is almost non-existent. In addition, completing the
trans-European Transport network will require at least two more decades of substantial
investment particularly in most of the Central and Eastern Member States.
The onset of the crisis led to major
reductions in the EU in trade and foreign direct investment, which are
important sources of growth for the less developed Member States. Fortunately,
exports of the EU-13 to other EU countries have shown significant recovery and
now account for a larger share of their GDP than before the crisis, while FDI
has also picked up.
Competitiveness remains low in most regions
in Central and Eastern Member States, though capital city regions are typically
the exceptions. These tend to be highly competitive, but for the most part they
do not as yet generate any measurable spill-overs to benefit other regions.
Most regions close to the capital in these countries, therefore, do not gain
perceptibly from their proximity, while in many more developed Member States
the regions neighbouring the capital also tend to have high levels of
competitiveness. Indeed, in some Member States, such as the Netherlands, Germany and Italy, other regions with an important second-tier city have a higher level
of competitiveness than the capital city region. 
Chapter 2: The crisis has wiped out half of
the employment gains made between 2000 and the onset of the recession,
particularly in the southern Member States. As a result, in transition and less
developed regions, employment rates are around 10 percentage points below the
national target as compared to only 3 percentage points below in the more
developed regions. Increases in unemployment have also been larger in these
regions, averaging 5 percentage points between 2008 and 2013 as against 3
percentage points in more developed regions.
Although 2013 was the first year in which
the average rate of unemployment in the EU was the same for women as for men,
big disparities remain in some parts, unemployment being much higher for women
than for men in many southern regions. Employment rates for women remain lower
than those of men in all EU regions. While the gap is relatively small in a
number of Swedish and Finnish regions, it is more than 20 percentage points in Italy, Greece, and several regions in Romania, the Czech Republic and Poland. On the educational
front, however, in nine out of ten regions more women than men aged 30-34 have
a tertiary-level qualification.
Higher risk of poverty and social exclusion
is another legacy of the economic crisis. There are now around 8 million people
at risk of poverty in the EU, the increase being particularly pronounced in Greece, Spain, Italy and the UK. A key issue is the variation within countries. The risk of poverty tends
to be much lower in cities than in the rest of the country in less developed
member States, while in cities in the more developed Member States, the reverse
is the case. Accordingly, in the latter, to meet the national Europe 2020
poverty targets requires a major reduction in the number of people at risk of
poverty or exclusion in urban centres, while in the less developed countries
the main challenge is to reduce the numbers at risk in more rural areas. 
The large disparities in employment, income
levels and social well-being are major factors underlying population movement
within the EU. In Central and Eastern Member States, there has been a tendency
over the past 20 years for people to move from rural areas to urban ones,
especially to the capital city, as well as to other parts of the EU. The
combination of a natural decline in population and outward migration has led to
a significant reduction of people living in rural regions in the EU-13 over the
past decade. In the EU-15, on the other hand, the population has risen on
average in rural regions because of net inward migration more than offsetting a
natural reduction in population. 
In the EU-15, over the past decade the
contribution of net inward migration to population growth was three times
larger than that of the natural increase. By contrast, in the EU-13, net
outward migration contributed twice as much to population decline as the
natural reduction.
Wide variations remain across the EU in
life expectancy and mortality rates. Life expectancy differs by more than 9
years between the 10 regions where it is highest and the 10 where it is lowest.
Equally, infant mortality and deaths from road accidents in relation to
population differ by a factor of four between the 10 best and worst performing
regions.
Chapter 3: The crisis has had mixed effects
on the environment. The reduction in economic activity and income has made it
easier to reduce greenhouse gas emissions; though energy efficiency has not
increased greatly so that this reduction may well be reversed when demand picks
up. The crisis has also reduced the cost of allowances for greenhouse gas
emissions in the European Trading Scheme, so depressing the economic incentives
to invest in energy efficiency and renewable energy and delaying the transition
to a low-carbon economy. The European Commission has postponed the auction of
some allowances in response to these low prices. 
Some progress has been made across the EU
in improving the treatment of urban wastewater and solid waste. More towns and
cities now meet the quality standards set in the EU Directive on urban
wastewater treatment and more solid waste is recycled, or incinerated with
energy recovery, and less is dumped in landfills. In both cases, however, more
needs to be done and substantial investment is still required particularly in
many of the less developed Member States and regions. 
The quality of the ‘services’ provided by
the eco-system differs substantially across the EU. The services concerned can
fulfil important functions such as cleaning air and water, retaining water to
reduce flood risks and removing carbon. The recent floods in many parts of the
EU and the low air quality in many cities underline the need for them. The
advantage of investing in such services is that it can often be cost-efficient
while helping to limit the loss of bio-diversity. 
The urban dimension of sustainable growth
is one of many contrasts. On the one hand, air quality is poor in many cities,
made worse by traffic congestion, and cities are more vulnerable to heat waves,
due to the ‘heat island’ effect, as well as to flooding because of their
proximity, in many cases, to rivers and the sea and the large expanse of sealed
surfaces. 
On the other hand, cities offer major
advantages in terms of eco-efficiency, since the close proximity of different
locations reduces the need to travel long distances. Public transport is also
more available in cities, offering a more energy-efficient means of travel, and
people living in cities on average use less energy to heat their housing.
Equally, cities use land much more efficiently than others areas where
population density is much lower and built-up land per inhabitant is much higher

Chapter 4: In most Member States, the
government budget has been in significant deficit over the crisis period and public
debt levels have risen dramatically, in some cases well above 100% of GDP. The
deterioration in public finances has led to the widespread implementation of fiscal
consolidation measures and many governments have cut back public investment
markedly. On average, public investment in the EU declined by 20% in real terms
between 2008 and 2013, in Greece, Spain and Ireland, by over 60% and in the
EU12 countries, where Cohesion Policy funding is particularly important, by
32%. This could well depress growth rates over the medium-term. 
As a result of the cut-backs in national
expenditure, there is increased reliance on Cohesion Policy to finance growth-enhancing
investment. In 2010-2012, Cohesion Policy funding was equivalent to 21% of
public investment in the EU as a whole, to 57% in the Cohesion countries taken
together and to over 75% in Slovakia, Hungary, Bulgaria and Lithuania. Without this funding, public investment in the less developed Member States
would have declined even further. 
Local and regional governments in the EU
are responsible for almost two thirds of all public investment and,
accordingly, the reductions which have occurred have had a big impact on them. The
political autonomy (or self-rule) of regions has tended to grow over the past
few decades, with substantial increases in many Member States. In Italy, in particular, the degree of self-rule in regions is now higher than in the Federal states of
 Germany, Austria and Belgium. 
Chapter 5: The EU has given increasing
attention to the importance of governance and the quality of public
institutions over the past few years, including in relation to Cohesion Policy
programmes. For example, an anti-corruption report has been adopted in 2014 and
many of the country-specific recommendations made as part of the European
Semester concern issues of administrative capacity. Initiatives, such as e-Government
and e-Procurement, can help both to increase efficiency and reduce the
opportunities for abuse of power. In addition the development of national
anti-corruption and anti-fraud strategies is likely to strengthen
administrative capacity and lead to funds being used more effectively.
As regards Cohesion Policy, improving
institutional capacity and public administration is one of the 11 key thematic
objectives for the period 2014-2020. One of the reasons for this is the
observed link between low levels of government efficiency and the absorption
rate of Cohesion Policy funding for the 2007-2013 period, which is so low in
some cases that there is a serious risk that Member States will lose
significant amounts of the funds available to them. 
While countries in the North of Europe
score well in surveys of governance and ease of doing business, there are still
too many Member States where the standard of public authorities is perceived to
be low and significant numbers of people report paying bribes. New research has
revealed that the ease of doing business and the quality of institutions also
vary in many cases within countries, which implies that more targeted
interventions may be needed to bring the situation in lagging regions up to
standard. Research has also indicated that governance problems can act as a
brake on social and economic development and limit the impact of Cohesion
Policy investment.
Recognising the key role of regional and
local authorities in public investment, the OECD has recently adopted principles
on the effective management of public investment which apply across all levels
of government.
Chapter 6: Cohesion Policy was born out of
concerns that obstacles to economic development, such as a lack of innovation,
labour force skills, infrastructure or institutional quality, will permanently
depress growth and productivity and lead to lower standards of living. Over the
years, the financial support under the policy, which has consistently focused
on less developed regions, has shifted away from investment in hard
infrastructure towards business support and innovation, employment and social inclusion
to overcome these obstacles.
The nature of Cohesion Policy and its
objectives have also evolved. The geographical coverage has been simplified,
with all regions being eligible for a measure of support, while in addition to
its focus on reducing economic disparities, the policy has become more closely
aligned with the overall strategy of the EU. Accordingly, in the 1990s, funding
was extended to environmental and trans-European transport infrastructure and
in the 2000s, Cohesion Policy was directed towards the pursuit of the Lisbon and Gothenburg strategies for growth and sustainable development. In the new
period, Cohesion Policy is an integral part of the Europe 2020 strategy with a
strong focus on employment, innovation, sustainability and reducing poverty and
social exclusion. 
Successive enlargements of the EU have
changed the challenges which Cohesion Policy has to confront and increased the
difficulty of tackling them. Not only have they led to a much greater number of
regions with low levels of development but they have also increased the
territorial diversity of the EU. 
With the introduction in the Lisbon Treaty
of territorial cohesion as an explicit objective of Cohesion Policy, a stronger
emphasis has been given to access to services, functional geography,
territorial analysis and sustainability. This shift is mirrored in the
increased focus on sustainable growth in Europe 2020 and in the recognition of
the importance of moving beyond GDP when assessing territorial development. The
debate on how to measure progress and the role of Cohesion Policy in this
respect is still ongoing. 
Chapter 7: Cohesion Policy in the 2007-2013
period made a substantial contribution to growth and jobs. It is estimated to
have increased GDP by 2.1% a year on average in Latvia, 1.8% a year in Lithuania and 1.7% a year in Poland in relation to what it would have been without the investment it
has funded. It is also estimated to have increased the level of employment, by
1% a year in Poland, 0.6% in Hungary, and 0.4% in Slovakia and Lithuania. The estimates of the longer-term effects are larger
because of the impact on the development potential of economies. In both Lithuania and Poland, GDP in 2020 is estimated to be over 4% above what it would be without the
investment concerned and in Latvia, 5% higher. 
Over the same period, Cohesion Policy has
been important in sustaining public expenditure in vital areas, such as
R&D, support for SMEs, sustainable energy, human resource development and
social inclusion. In some Member States, it also helped further national reform
efforts, especially as regards education systems, the labour market and public
administration. 
There is clear evidence that the policy is producing tangible
results in many areas. Support had been provided to over 60 000 RTD
projects by the end of 2012, over 21 500 co-operation ventures between
enterprises and research centres, and almost 80 000 business start-ups. In
addition, the funds had provided over 5 million more people with access to broadband,
3.3 million with an improved supply of drinking water and 5.5 million with main
drainage and a connection to waste water treatment facilities. 
Between 2007 and 2012, the policy has supported up to 68 million
individual participations in labour market programmes[1], 35 million of them
involving women, 21 million young people, 22 million unemployed
and nearly 27 million of those with low levels of education (compulsory
schooling or below). The ESF helped 5.7 million people find employment and
almost 8.6 million to obtain qualifications, while Member States reported that
it had contributed to over 400,000 business start-ups or people becoming
self-employed. 
Major results are still expected from the 2007-2013
programmes over the remaining months up to the end of 2015. The payments data
however underline the need to step up the completion of these programmes. Although
there is an inevitable delay between expenditure on the ground and Commission
payments being made, there is evidence of serious delays in a number of
countries in projects being selected for support and being carried out. This is
especially the case in areas such as RTDI, rail, ICT and broadband and
investment in both renewable energy and energy saving, where authorities have limited
experience or projects are relatively complex. 
Chapter 8: In 2014-20, a third of the EU Budget
will be invested under Cohesion Policy to help address disparities between regions
while at the same time contributing to the achievement of the Europe 2020
goals. The two objectives are fully compatible with each other. Indeed, the
pursuit of the Europe 2020 goals can be seen as a means of furthering regional
development aims and of strengthening the various elements which determine the
growth potential of regions. 
The new Cohesion Policy is not only fully
aligned with the Europe 2020 strategy and its headline targets but it is also
linked to the European semester and the EU economic governance process. This
will ensure that the effectiveness of investment is not undermined by unsound
economic and fiscal policies. Member States and regions are also required to
put in place sound regulatory, administrative and institutional frameworks to
maximise the impact of investment. Together with a concentration of resources
on a few key priorities and a stronger focus on performance and results, it
will increase value for money and the contribution of Cohesion Policy to growth
and job creation.
[1]       Reporting counts all instances of participation and many
people may have participated several times. Participations can range from a
short interview, to counselling, training or work experience. 
Chapter 1: Smart Growth

1.     Introduction

Cohesion Policy has invested heavily in
smart growth over past decades. It has co-financed innovation, education and
digital and transport networks. This investment has helped to create a single
market that boosts growth, productivity and specialisation in all regions and
which, accordingly, strengthens the position of the EU in global markets where
it has to compete with both low-cost locations and highly innovative
competitors.
This chapter describes the trends relating
to smart growth in regions and cities in the EU and highlights the impact of
the crisis on them. It covers a wide range of topics, including the territorial
dimension of the crisis, innovation, tertiary education, entrepreneurship, the
extension of digital and transport networks and market integration through
trade and foreign direct investment.
The main concern throughout is to highlight
the performance of the less developed regions and particular types of area such
as cities and rural areas. The concern is also with the pursuit of the Europe
2020 national targets for R&D expenditure, tertiary education and lifelong
learning.
Most of the long-term trends reported here
are positive in terms of the performance of the EU economies. They include
closer integration of markets, trade and FDI, the shift of employment to more
productive sectors, better access to digital and transport networks and
continuing increases in the number of people with tertiary education.
The crisis, however, has been highly disruptive
in many parts of the EU. It has reversed the long-term trend towards a
narrowing of regional disparities. It has led to reductions in economic
activity and employment in most Member States. Fortunately, the first signs of
recovery can be detected in several of the aspects analysed here, such as
increases in trade and positive GDP growth in the latter part of 2013 in almost
all EU Member States.
Although Cohesion Policy has made a
substantial contribution to smart growth and reducing disparities, the low
levels of innovation in many regions, the economic disparities which remain and
the gaps in the physical and digital networks still require substantial amounts
of investment in the coming years and beyond the present programming period.

2.     The crisis suspended the
reduction in regional disparities

One in four EU residents, live in (NUTS 2)
regions with a GDP per head in PPS terms[1]
below 75% of the EU average (see map). Most of these regions are located in
central and eastern European Member States, but also in Greece, Southern Italy, Portugal and most of the outermost regions.
Map 1 GDP per
head (PPS), 2011
Between 2000 and 2011, all the regions in
the central and eastern Member States recorded an increase in GDP per head in
PPS relative to the EU average. The biggest increases were typically in the
capital city regions. Indeed, in these regions in Slovakia, Romania and Bulgaria, GDP per head in PPS terms increased markedly (to 186% of the EU average in the
first, 122% in the second and 78% in the third), in the first two countries by more
than double the national average increase. In the less developed regions in
Greece, Italy and Portugal (except Açores), however, there was no increase in GDP
per head relative to the EU average, due in Greece to the severe effect of the
crisis , but in the other two, partly to their growth rates being relatively
low before the crisis.
Until the crisis in 2008, disparities
between regional economies in the EU were shrinking (the coefficient of variation
of regional GDP per head fell by 10% between 2000 and 2008 - Figure 1). In
2000, average GDP per head in the most developed 20% of regions was about 3.5
higher than that in the least developed 20%. By 2008, the difference had narrowed
fallen to 2.8 times. This was mainly due to the regions with the lowest GDP per
head growing faster than average and catching up with the more prosperous ones
(a process known as Beta convergence). However, the crisis seems to have
brought this tendency to an end and between 2008 and 2011, regional disparities
widened (the coefficient of variation increased slightly).
This break in the trend towards convergence
is confirmed by other economic indicators for which more recent data are
available, in particular for employment and unemployment. While regional
disparities in both employment and unemployment rates narrowed between 2000 and
2007, they have widened significantly since 2008. In 2013, therefore,
disparities in both were wider than in 2000.
Figure 1: Coefficient of
variation (2000 = 100), GDP per head,
employment rate, unemployment rate, EU-27 NUTS 2 regions, 2000-2012
Source: EUROSTAT
database. - DG REGIO's calculation.
These changes can also be seen in the real growth
rates of GDP per head. Virtually all regions had positive growth between 2001
and 2008, with rates of more than 5% a year in many regions in the EU-13.
Between 2008 and 2011, two out of three regions experienced a reduction in GDP
per head, amounting to over 3% a year  in Greece and in regions in Romania, the UK and Ireland.
 Map 2 Growth of GDP per head in real terms, 2001-2008 || Map 3 Growth of GDP per head in real terms, 2008-2011 
Regional disparities have widened during
the last few years because the economic crisis has affected regions
differentially. Some regions have been hit severely, others hardly at all. This
is particularly evident with regard to regional unemployment rates. In 2008,
five regions had an unemployment rate above 20%. In 2013, the number had
increased to 27. At the same time, unemployment has gone down in many German
regions because of the relatively strong performance of the German economy
since the global recession in 2008-2009. 
Even though the latest figures available for
regional GDP per head show only the start of the crisis, the same pattern is
evident. In some regions, GDP per head in real terms (i.e. at constant prices)
declined considerably, as, for instance, in Közép-Dunántúl (Hungary) or in Estonia, where it fell by 15% between 2008 and 2009. In others, it continued to
increase, as in Pomorskie (Poland) or Åland (Finland), where it rose by 4% and
6%, respectively. 
The impact of the global recession
following the financial crisis of 2008 had no clear geographical pattern,
affecting both more and less developed economies. Between 2008 and 2009, real
GDP per head fell markedly in the three Baltic States but also in Finland, Sweden and Italy. Equally, the fall in real GDP per head was relatively small in France and Belgium but also in Cyprus and Malta, while there was continued growth in Poland. Of the 13 regions in which real GDP per head fell by more than 10%, 6 had a GDP per
head above the EU average in 2008.
Regional disparities within countries also
widened significantly in a number of cases between 2000 and 2011. This was
particularly so in Bulgaria and in Romania (where the coefficient of variation
increased by 22 percentage points and 12 percentage points, respectively),
mainly because of the high growth rate in the capital city region. While GDP
per head in the other regions in the two countries still converged towards the
EU average, it was at a much slower rate. 
Regional disparities also widened in Greece
and the UK over these 11 years (the coefficient of variation increasing by 12
and 8 percentage points, respectively) but in both cases partly because GDP per
head declined relative to the EU average in a number of less developed regions,.
This was so, for example, in Ipeiros (Greece), where it declined from 71% of
the EU average to 55%, and in West Wales and the Valleys (in the UK), where it
fell from 72% of the EU average to 64%.
Another indicator of regional disparities,
the Theil index[2],
can be decomposed into a component which measures disparities between Member
States and one which measures disparities within them. The index shows that
disparities in GDP per head between NUTS 2 regions within Member States (which
can only be calculated up to 2011 from the data available) have increased
slightly since .2004, which to a large extent reflects the high rate of growth in
a number of urban areas (typically capital city regions) in the EU-13 (Figure
2). This was offset by the marked reduction in disparities between Member
States up until 2009, so leading to an overall reduction in regional
disparities in the EU-28. The economic crisis interrupted this process of convergence,
with disparities remaining unchanged in 2009 and increasing in 2010 and 2011.
However, national accounts data for 2012 and the latest forecasts at the Member State level up to 2015 suggest that this interruption might only be temporary and
that there may already have been a resumption of the process of convergence in
2012, so long as there was no significant increase in regional disparities
within countries.
Figure 2: Theil index, GDP per head, EU-28 NUTS 2 regions,
2000-2015
Source: EUROSTAT database.
DG REGIO's calculation.         
The effect of the economic crisis on the
long-run process of regional disparities in the EU narrowing can also be seen
in the experience of individual regions.. Between 2003 and 2011, 50 of the 63 regions
in the less developed or moderately developed Member States recorded a higher growth
rate than the EU average (Figure 3). In the period prior to the crisis
(2003-2008), 56 of these regions grew faster than the EU average, while during
the crisis (2009-2011), this number dropped to 45.
Figure 3: GDP per head growth rates of regions in less
developed or moderately developed Member States, 2003-2011
Source: EUROSTAT
database. DG REGIO's calculations. Bars represent regions. No data for Greece. 
There are grounds for believing that the long-run
convergence process in the EU will continue after the crisis comes to an end.
Since the process is driven in part by less developed regions adopting technology
and methods of working developed and tested in other regions, it means that
they tend to catch up in terms of productivity. This process, assisted by
investment funded under Cohesion Policy, is likely to see growth in less
developed regions return to a higher rate than in the more developed parts of
the EU in the years to come, just as over the period 2003-2008.
Analysis of changes in GDP per head between
2000 and 2011 confirms that, in the long run, convergence is mostly a result of
the least developed regions catching up rather than growth declining in the
more developed ones. For example, 37 (NUTS 2) regions had a GDP per head below
50% of the EU average in 2000 but only 20 in 2011, with GDP per head in 16 regions
increasing to between 50% and 75% of the EU average and in one region
(Yugozapaden, the capital city region in Bulgaria) to between 75% and 100% of
the average. The pace of convergence in Bucureşti–Ilfov (Romania) between 1995 and 2011 was also remarkable, its GDP per head increasing from below
50% of the EU average to over 120%. 
GDP per head grew faster in real terms in 
the less developed Member States over the period 2000-2013 and is forecast to continue
to do so in 2014 and 2015 (see Figure). The rate of growth in the moderately
developed Member States, however, fell below that in the highly developed
Member States in 2010 and continued to be lower in 2011-2013 but is forecast to
be slightly higher by 2015.
Figure 4: Growth of GDP per head in real terms,
2001-2015
 .
 Map 4 NAFTA GDP per head, 2012 || Map 5 Russia, India, China and Brazil, GDP per head, 2010 

Box on regional economic disparities in the world

Large regional economic disparities can be
found in the BRICs (Map 5) as well as in the North American Free Trade
Agreement Area (Map 4). The disparities cannot be directly compared to those in
 Europe as the size of the regions differs too much. India and China both with a population of more than a billion would need more than 700 regions to be
comparable with NUTS-2 regions in the EU. For the US, GDP per head should relate
to 160 regions instead of 50 States to be comparable.
The North American Free Trade Agreement has
faciliated closer economic integration between Canada,
the US and Mexico since 1994 through increased trade and foreign direct
investment. Unlike the EU, NAFTA does not involve freedom of movement of
people. As a result, many of the Mexicans working in the US are illegal immigrants.
During the first decade of the agreement
(1994-2003), real GDP per head growth in Mexico averaged only 0.8% a year. The
rate was three times higher in Canada and the US over the same period. The low
overall growth rate in Mexico was due not to the free trade agreement but possibly
to low education levels, an unfavourable business environment and a lack of transport
infrastructure. As NAFTA does not have a development policy like Cohesion Policy,
it takes much longer for Mexican regions to benefit from trade integration.
Between 2004 and 2012, however, the Mexican
economy performed better with real GDP per head growth averaging 1.5% a year despite
the crisis, double the rate in Canada and the US. 
Despite the stronger economic performance of Mexico, there was no reduction in regional disparities in NAFTA. In large part, this is
because many of the less developed Mexican regions were not able to catch up. 
Although regional disparities tend to widen in
the first phases of economic development, this was not the case in the BRICs. Between 2000 and 2010, disparities narrowed in China and Brazil, though they widened in India and Russia.
In China, the coastal regions have a much
higher GDP per head than the more inland regions. In Russia, Moscow and Saint Petersburg and the surrounding regions have a much higher GDP per head than the regions in the south of the country. More generally,
GDP per head in the north tends to be higher than in the south because of the
extraction of natural resources. Brazil and India also have large regional
disparities, their main urban areas having a much higher GDP per head than the
more remote rural regions. 
As these countries have sought new ways of
reducing regional disparities, they have become more interested in how Cohesion
Policy operates. In the last 8 years, the Commission has signed memoranda of
understanding on regional policy cooperation with China, Russia and Brazil and cooperation agreements with Chile, Peru and Japan as well as Ukraine, Moldova and   Georgia under the Eastern Partnership. As part of the latter, the Commission
has organised activities in respect of regional and urban policy which have led
to exchanges on technical assistance, studies, study visits, training courses,
conferences, network building and contacts between regions and cities in the EU
and these other countries.

Box on Turkey

Turkey has a population
of 75 million which is growing fast (by nearly 10 million over the past
decade). The economy is also growing fast, by 5% a year between 2002 and 2012.
As a result, GDP per head in PPS terms had risen to 56% of the EU average in
the latter year, higher than in Romania or Bulgaria, but below that in Croatia.
There are, however, wide regional disparities.
The western regions of Istanbul (50% above the national average in 2011),
Kocaeli (41% above), Ankara (32% above) and Bursa (31% above) have relatively
high levels of GDP per head. Three eastern regions have levels which are less
than half the national average. These disparities widened between 2004 and 2007
but narrowed a little between 2007 and 2011. 
The agricultural sector still accounts for
almost a quarter of total employment and for a significant, though much
smaller, share of GDP (9% in 2012).
Map 6: Turkey, GVA per head 2010

Box on Western Balkan

There are three candidate countries in the
Western Balkans (Montenegro, Serbia and the Former Yugoslav Republic of
 Macedonia) and three potential candidate countries (Albania,
Bosnia-Herzegovina and Kosovo – as defined under UN Security Resolution 1244). 
Montenegro has the
smallest population, of around 620,000, but the highest GDP per head (if only
46% of the EU average in PPS terms in 2012) and the second lowest rate of
unemployment (20%). 
Serbia has the largest
population (7 million) and the biggest economy. GDP grew by 6% a year between
2003 and 2008 but growth fell to 1.2% a year between 2008 and 2012. GDP per
head is only a third of the EU average and unemployment was 24% of the labour
force in 2012. 
The Former Yugoslav Republic of Macedonia has a
population just over 2 million. Its GDP grew by 5% a year between 2003 and 2008
and by 2% over the subsequent four years. The unemployment rate is very high
(31% in 2012) and GDP per head similar to that in Serbia (35% of the EU
average).
The three potential candidate countries had a
GDP per head of between 23% and 30% of the EU average in PPS terms in 2012. Albania had the lowest unemployment rate (14%) which was still well above the EU average,
while rates in Bosnia-Herzegovina (29%) and Kosovo (35%) were very much further
above the average.
Only one of the 6 countries (Albania) has an employment rate above 50% of the population aged 15-64 (in the EU, no Member State has a rate below 50%). In Bosnia-Herzegovina, it was only 40% in 2012 and in
Kosovo, less than a quarter of working-age population were employed, which is
remarkable.
Table 1: Key indicators for Western Balkan,
2003-2012
   || Population (in 1000s) || GDP per head in PPS (EU-28=100) || Unemployment rate (%) || Employment rate, aged 15-64 (%) || Real GDP growth rate (%) 
   || 2012 || 2012 || 2012 || 2012 || 2003-2008 || 2008-2012 
 Montenegro ||  621,240 || 43 || 20 || 47 || 6.2 || 1.2 
 Former Yugoslav Republic of Macedonia ||  2,059,794 || 35 || 31 || 44 || 4.7 || 1.9 
 Serbia ||  7,216,649 || 35 || 24 || 45 || 5 || 0.2 
   ||   ||   ||   ||   ||   ||   
 Albania ||  2,815,749 || 30 || 14 || 56 || 6 || 3.8 
 Bosnia and Herzegovina ||  3,836,000 || 28 || 29 || 40 || 5.2 || 0.6 
 Kosovo (under UN Security Resolution 1244) ||  1,815,606 || 23 || 35 || 24 ||   || 4.6 * 
 Source: Eurostat  * 2008-2011 ||   ||   ||   ||   

3.     Central and eastern Member
States maintain a strong industrial sector, but their agriculture needs to
continue to modernise

In 1970, the industrial
sector accounted for over 30% of total employment and GVA (gross value-added) in
the EU-6 (i.e. the 6 Member States at the time). The rise of the service
sector, the automation of manufacturing and the relocation of parts of
manufacturing to emerging economies has led to a steady reduction in the share
of employment and GVA in industry (excluding construction) in the EU economy
(see figure). This trend was not affected by the enlargements up to those in
2004 and 2007 which both led to a small increase in the share of employment in
industry. By 2012, the share of GVA in industry had fallen to 19% and the share
of employment to 16%.
In the EU-12, however,
the share of industry is larger than in the EU-15 and has changed less over
time. The share of GVA in industry remained at around 27% between 1995 and
2012. The share of employment declined from 26% to 22% over these 17 years, but
it remains much larger than in the EU-15, where only 14% of total employment is
in industry (Figure 5).
Figure 5
Industry (excluding construction) in the EU, 1970-2012

Source Ameco
The change in the share of agriculture has
been substantial. In 1970, it accounted for 12% of total employment and 6% of
GVA in the EU-6. By 2012, the shares in the EU-27 had fallen to 5% and 2%,
respectively. The effect of the various enlargements is more visible in this case,
with increases in the employment share after the enlargements of 1981, 1986,
2004 and 2007. Because of the low level of productivity in agriculture in the
countries joining the EU, however, its share of GVA did not increase
significantly - subsistence farming, for example, contributes to employment in
agriculture but hardly at all to GVA.
In the EU-12, the share of employment in
agriculture fell from 25% to 15% between 1995 and 2012 and as productivity
increases, it is likely that it will fall further. In the EU-15, it was only 3%
in 2012.
 Figure 6 Industry (excluding construction) in the EU-12, 1995-2012 Source ESTAT || Figure 7 Agriculture in the EU-12, 1995-2012 Source ESTAT 
Figure 8: Agriculture in the EU, 1970-2012

Source: AMECO and ESTAT
As the number of jobs in agriculture and
industry declined, more jobs were created in services. However to switch from a
job in agriculture or industry to one in services often requires learning a
whole new set of skills. Providing training to people who want to find a job in
a different sector can help to ease this transition.

4.     Construction and industry
most hit by the crisis 

The less developed
Member States tend to have a different economic structure than the rest of the
EU with more employment and GVA in industry (see table). In 2012, the share of
employment in industry in these countries was 22%, 50% larger than in highly
developed Member States (15%). There is little sign of convergence in this
share. Industry in the less developed Member States showed higher growth of GVA
than other sectors between 2000 and 2012. Even over the crisis period, 2008 to
2012, it grew by 2% a year while it declined by 1% a year in both moderately
developed and highly developed Member States. Employment in industry also
remained broadly unchanged up until 2008 in the less developed Member States,
while it declined in the others. 
Joining the EU and the
single market has created more potential for specialisation and spatial
clustering. Less developed Member States, therefore, may have been able to
maintain a larger share of employment in industry because the balance between
labour costs, productivity and accessibility created an attractive location for
manufacturers. 
Employment and GVA in
construction has fallen sharply over the crisis period in all three country
groups. The reduction was largest in the three Baltic States, Ireland, Greece and Spain, in all six of which a large real estate bubble burst as the financial
crisis hit 
Financial and business
services account for considerably smaller shares of employment and GVA in the
less developed Member States, but they are increasing slowly towards those in
the highly developed countries. The impact of the crisis on the combined sector
in less developed Member States was limited, both employment and GVA continuing
to grow, but at slower rates than between 2000 and 2008.
The restructuring and
modernisation of the agricultural sector is still ongoing in the less developed
Member States. In 2012, the sector accounted for 16% of total employment, over
6 times more than in highly developed Member States (2.5%). The share of GVA in
agriculture was considerably smaller but three times larger than in the latter
countries (4.5% as against 1.5%). Both shares are tending to decline as
employment continues to shrink and growth of GVA lags behind that in other
sectors. It was still the case, however, that the share of employment in
agriculture in less developed Member States in 2012 was larger than in the EU-6
in 1970 (12%). 
The impact of the
crisis was more severe for the moderately developed Member States, GVA and employment declining by over 2% a year between 2008 and 2012. The reduction was
especially large in construction, manufacturing, distribution, transport and
communications.
Overall, the highly
developed Member States were less affected by the crisis, employment declining
by just 0.4% a year and GVA by 0.2% a year between 2008 and 2012 (see table).
The biggest reduction in both employment and GVA were in construction,
manufacturing and agriculture.
 
Table 2 Change in employment and GVA by sector per
group of member states, 2000-2012
[1]     The Gross Domestic Product (GDP) per head in Purchasing Power
Standards is the total value of all goods and services produced per inhabitant.
Purchasing Power Standards (PPS) adjusts for differences between countries in
purchasing power due to differences in price levels.
[2]       The Theil index essentially measures the extent to which the
inequality of GDP per head between regions differs from the situation where
every region has the same level.

5.     The crisis led to employment losses, but also some
productivity gains 

Between 2001 and 2008,
GVA per head in the EU grew by 1.7% a year in real terms, primarily fuelled by
productivity growth of 1.2% a year. Increases in the employment rate added another
0.5% a year while a rise in the share of working-age population in the total
had a small but positive impact (0.1% - Table 2). Over the crisis period of
2008-2012, GVA per head fell by 0.5% a year and the employment rate by 0.8% a
year with productivity growing by 0.3% a year.
The difference between
the less developed Member States and the rest of the EU was pronounced in both
periods. Between 2001 and 2008, growth of GVA per head was much higher (5.2% a
year), primarily because of productivity growth (4.2% a year), while an
increase in the share of working-age population in the total (which increases
the number employed at any given employment rate) also contributed
significantly (by 0.4% a year). Over the period 2008- 2012, GVA per head in the
less developed Member States as a group increased, but at a much lower average
rate (by 1.2% a year), while it declined in virtually all other Member States.
The main source of growth during these years was productivity (which increased
by 1.8% a year) while employment declined significantly (by 1.1% a year).
All of the less
developed Member States experienced losses in employment between 2008 and 2012
and gains in productivity, except Romania and Hungary where the opposite was
the case (Table 2). In five of the countries, productivity growth compensated
for the reduction in employment and GVA per head remained unchanged. The effect
of the rise in the share of working-age population in total was smaller during
this period (adding 0.2% a year to growth instead of 0.4%), but it was still
significant in Bulgaria, Poland and Slovakia (adding between 0.4% a year and
0.5% a year). In Croatia, there was a fall in working-age population relative
to the total (reducing GVA per head by 0.6% a year) because of a combination of
outward migration, low fertility rates and ageing. 
GVA per head grew by
1.3% a year between 2001 and 2008 in the highly developed Member States, but
declined by -0.7% a year between 2008 and 2012. In the first period,
productivity growth (increasing by 0.9% a year) contributed more than the increase
in the employment rate (of 0.4% a year), with the share of working-age
population in the total remaining unchanged. Between 2008 and 2012, the
employment rate declined (by 0.7%a year), while productivity increased only
marginally and the share of population of working-age fell equally marginally
on average, though by more (by around 0.5% a year) in Ireland, Denmark and   Finland.
Among the
highly-developed Member States, Ireland and Spain stand out as having suffered
the biggest reduction in employment rates (by 3.6% and 3.9% a year) and having
the highest productivity growth (2.4% a year and 2.7%). This is in part due to
the collapse of construction, a sector with low productivity, though also to
productivity gains in other sectors. 
Germany and Sweden were the only two highly-developed Member States to
experience an increase in GVA per head over the crisis period, but with a very
different division between productivity and employment. In Germany, therefore, employment (taking the employment rate and share of working-age
population together) increased by slightly more than GVA per head, effectively
because of a small decline in productivity. In Sweden, productivity increased
by more than GVA per head and the employment rate fell.
The moderately
developed Member States (which include Greece, Portugal, Cyprus, Malta, Czech  Republic and Slovenia) have been affected more strongly as a group by the
crisis than the other Member States. While GVA per head grew by 2.7% a year in
the first period, it shrank by 2.5% a year in the second, primarily due to
reductions in the employment rate (by2% a year), but also to a decline in the
share of working age population in the total (by 0.3% a year) and a fall in
productivity (by 0.2% a year). The latter fall, therefore, cushioned the effect
of the reduction in GVA on employment but only a little. There were, however,
very different patterns of development over this period in the different
countries. 
In Malta, GVA per head increased slightly, the only country in the group where this was the
case, but a relatively large decline in productivity (by 0.8% a year) was
accompanied by a significant rise in the employment rate (by 1.2% a year). In
Portugal, on the other hand, GVA per head declined but by less than the average
in the group while productivity increased by much more than in the rest of the
group by 1.8% a year), so that the employment rate fell significantly (by 2.4%
a year). In Cyprus, GVA per head fell markedly (by 3.2% a year), but
productivity increased (by 0.4% a year) unlike in the other countries in the
group (Greece and Slovenia), which combined with a large rise in working-age
population relative to the total by 0.8% a year), due to inward migration, led
to the employment rate falling considerably (by 4.4% a year, more than in any
other country).
Box on Decomposing growth in GVA per head
Growth in GVA per head is broken down into three main components:
changes in productivity (GVA per person employed), changes in the employment
rate (Employment relative to population of working age) and changes in the
share of working age population in the total.
Accordingly:
The same identity can be expressed in terms of changes.
Usually, the employment rate is derived from the Labour Force Survey
and is based on the place of residence of the person employed. Productivity, on
the other hand, is calculated on the basis of employment at the place of work
(from the national accounts). To ensure that this simple identity holds, the
employment rate here is based on employment reported in the national accounts
rather than the Labour Force Survey. 
Table 1: Decomposing average annual change in GVA
per head per MS, 2001-2008 and 2008-2012

6.     Growth in metropolitan regions
more prone to booms and Busts than in rural regions
6.1.    Capital metropolitan regions performed well until the crisis
led to above average employment losses

In 2011, metropolitan regions (see map 7)
accounted for 59% of EU population, 62% of EU employment and 67% of EU GDP.
Accordingly, they are major centres of employment and of business activity
which have a higher level of productivity than elsewhere. In all Member States,
GDP per head is higher in metropolitan regions than in other regions, though
this does not always translate into higher growth rates. For example, between
2000 and 2011, GDP per head grew faster in non-metropolitan regions in Germany, Austria, Sweden, Finland, Portugal and Spain. 
Nevertheless, in both the EU-15 and EU-13, real
GDP per head in metropolitan regions grew faster than in other regions between
2000 and 2008 (see table). Growth rates in capital city regions were especially
high, partly because of their higher productivity growth in the EU-15 and
higher employment growth in the EU-13.
Growth in second-tier metropolitan regions was the
same as at the national level, but below the rate in the capital metropolitan regions.
Smaller metropolitan regions grew more slowly than the other metropolitan
regions. In the EU-15, they had the same rate of growth as in non-metropolitan
regions. In the EU-13, the smaller metropolitan regions had a significantly
lower rate of growth than the non-metropolitan ones. 
The crisis had a different effect on the
metropolitan regions in the EU-15 and the EU-13 between 2008 and 2011. In the
EU-15, GDP in the capital metropolitan regions declined at the same rate as in other
regions. In the EU-13, GDP in the capital metropolitan regions declined, while it
grew in the other regions. In both cases, this was accompanied by  a larger reduction
in employment than elsewhere. 
In the EU-15, in second-tier and smaller
metropolitan regions, productivity growth was low and employment declined, the
fall in GDP per head being similar to that in the EU-15 as a whole. 
In the EU-13, in second-tier and smaller
metropolitan regions growth of GDP per head was twice the EU-13 average as a
result of high  productivity growth and no reduction in employment. It will be
interesting to see whether this launches a period of higher growth rates
outside the capital metropolitan regions leading to a narrowing of the gap in
GDP per head with the latter.
Table 2 Change in GDP per head, productivity and
employment per head by type of metropolitan region, 2000-2008 and 2008-2011
A new ESPON study[1] specifically examining the
performance of second-tier cities concluded that although some of these make a
substantial contribution to the national economy, in most countries, they do
not contribute as much as capital cities. It is argued that they could
contribute more, however, if they were given greater EU and national support. 
The tendency to over-invest in the capitals and
under-invest in second-tier cities is shown to be strong in many countries and
it is arguable that higher level governments should resist this tendency and create
territorial policies specifically for second-tier cities. This highlights the
importance of a tailored, place-based development policy and of taking explicit
account of the different territorial impact of national policies on R&D, innovation,
education and skills and transport and connectivity.
  City size, agglomeration benefits and metropolitan governance In all OECD countries, productivity and wages increase with city size (Figure 7). As a result of their high levels of productivity and their sheer size, large urban agglomerations contribute substantially to national growth. Figure 1: Larger metropolitan areas are more productive Source: OECD Metropolitan Database Why are larger cities more productive? The productivity of cities depends on a great many factors, such as having companies which are innovative and skilled workers. Productivity, however, at least up to a certain point, increases with the size of cities, which raises the question of why. The reasons are, first, that larger cities tend to have higher levels of human capital, even though the relationship with city size is often non-linear, in the sense that the shares of both very high skilled workers and low skilled increase at the same time. Secondly, larger cities typically have a larger share of high productivity sectors such as consulting and legal and financial services. Thirdly, larger cities are more likely to be hubs or service centres through which trade, finance and other flows are channelled. These flows typically require the provision of high value-added services. Fourthly, cities profit from ’agglomeration benefits‘, which means that, on average, the productivity of a person increases with the size of the city in which they live and work. Figure 10 shows productivity levels for cities in Germany and the US adjusted for difference in levels of human capital. Recent OECD estimates suggest that productivity increases by 2-5% for every doubling of the population (Ahrend, Farchy, Kaplanis and Lembcke, 2014), which is in line with similar studies for individual countries (Combes et al., 2011). Figure 2: Population size and productivity by city Germany || United States 
 || 
Source: Ahrend,
  Farchy, Kaplanis and Lembcke, 2014 
Agglomeration
  benefits are usually thought to arise from ‘sharing’, ‘matching’ and
  ‘learning’ (see, e.g., Duranton and Puga, 2004). In larger agglomerations,
  firms profit from a greater supply of local public goods, as well as
  ’shared’, or common, facilities such as public laboratories and universities.
  It is also easier for them to find suppliers that more closely match their
  needs. Similarly, a larger labour market allows a higher level of flexibility
  and workers to be better matched to jobs. Equally, the easier generation,
  diffusion and accumulation of knowledge in larger agglomerations facilitates
  access to technologies and skills. In addition, agglomeration benefits are
  often thought
  to be related to people being better ‘connected’ in larger cities and to
  arise perhaps from higher levels of “knowledge based capital” (intangible
  assets) in the firms located there.
Agglomeration benefits not only arise from the size
  of population in a city itself but they can also be ’borrowed; from
  neighbouring agglomerations. For every doubling of the population living in
  agglomerations within a 300 km radius, the productivity of the city in the
  centre is estimated to increase by 1-1.5% (Ahrend, Farchy, Kaplanis and
  Lembcke, 2014). This might explain why in the US productivity in urban
  agglomerations generally increases more strongly with population size than in
  European countries. Essentially, because distances between agglomerations
  tend to be less in Europe, smaller cities are not so disadvantaged since they
  ‘borrow’ agglomeration benefits from neighbouring towns and cities. 
The role of
  metropolitan governance structures in economic efficiency and well-being
Metropolitan areas typically span a number of
  administrative boundaries. They, therefore, often suffer from fragmented
  policymaking, and it is not uncommon for there to be several hundred local
  authorities. If these are left to pursue policies independently of each
  other, they are unlikely to tackle the challenge of developing the economic
  potential of the metropolitan area as a whole and the well-being of the
  people living there in an adequate way. Research undertaken by the OECD shows
  that municipal fragmentation does indeed reduce economic growth (see Figure 9)
  as well as the productivity of metropolitan areas, estimates indicating that
  a doubling of the number of municipalities per 100,000 people is associated
  with a reduction if 5-6% in productivity. It is likely that this in part is a
  result of sub-optimal provision of transport infrastructure, exemplified by
  routes in many Metropolitan areas ending at administrative boundaries for no
  apparent reason. This can also increase the possibility of those living in
  badly connected areas being socially excluded. 
Figure 3: Less fragmented metropolitan areas have experienced
  higher growth
Annual average
  GDP per capita growth, 2000-2010
Source:
  Ahrend and Lembcke (2014)
The potentially adverse effects of the fragmentation
  of municipalities, however, can at least be mitigated to a large extent by
  governance arrangements. More specifically, the existence of a central
  metropolitan governance body is estimated to reduce the adverse effect of
  fragmentation on productivity by around a half (Ahrend, Farchy, Kaplanis, and
  Lembcke, 2014). Metropolitan areas with a central governance body, on
  average, experience less urban sprawl, possibly as a result of more efficient
  use of land and the planning of transport (Figure 10). Similarly, in
  metropolitan areas with a transport authority, or some other body to
  coordinate transport, people tend to much more satisfied with the public
  transport system; the areas concerned also tend to have significantly lower
  levels of air pollution (Kim, Schuman and Ahrend, 2014).
Figure 4: Governance institutions and selected outcomes
 Central governance bodies and urban sprawl || Transport authorities and satisfaction with public transport 
 || 
Source:
  Ahrend, Gamper and Schumann, 2014
* Controlling
  for country fixed effects. 
Ahrend, R., Farchy, E., Kaplanis, I. and A. Lembcke, 2014, What Makes Cities More Productive?
  Evidence on the Role of Urban Governance for OECD Countries, OECD Regional Development Working Papers, forthcoming.
Ahrend, R., Gamper, C. and A. Schuhmann, 2014,
  The OECD Metropolitan Governance Survey: A Quantitative Description of
  Governance Structures in Large Urban Areas, OECD Regional Development
  Working Papers, forthcoming.
Ahrend, R. and A. Lembcke, 2014, Economic and Demographic
  Trends in Cities, OECD Regional Development
  Working Papers, forthcoming.
Combes, P.-P., Duranton, G. and L. Gobillon, 2011, The
  identification of agglomeration economies, Journal of Economic Geography,
  Vol. 11, pp. 253-266
Duranton, G., Puga, D., 2004. Microfoundations
  of urban agglomeration economies, in: Henderson, V., Thisse, J. F.,
  (Eds.) Handbook of Regional and Urban Economics, vol. 4. Amsterdam: NorthHolland, pp.2063–2117.
Kim, S.-J., A. Schumann, and R. Ahrend, 2014, What
  Governance for Metropolitan Areas?, OECD Regional Development Working
  Papers, forthcoming.

6.2.    GDP growth in rural regions was lower prior to the crisis,
but proved more resilient during the crisis years

Between 2000 and 2008, real GDP per head in
rural regions (see Map and box) in the EU-28 grew by 1.7% a year (Table),
similar to the rate in other types of region. The only difference was that
productivity in rural region grew faster, while employment relative to
population (i.e. the employment rate) rose more slowly.
In the EU-15, GDP per head in rural regions
grew slightly more slowly as productivity growth was lower than in other
regions, but the employment rate increased at the same rate as in other
regions.
In the EU-13, GDP per head in rural regions
also grew more slowly between 2000 and 2008 than in other regions, though here
productivity growth was higher and employment contracted relative to population
whereas in other regions, it increased. The two tendencies may be linked,
insofar as the higher productivity growth was due to catching up in the use of
technology and more efficient methods of working, including in agriculture,
which in turn led to a reduction in employment. 
The crisis had a differentiated effect on rural
regions. The reduction in GDP per head between 2008 and 2011 was less
pronounced in rural regions than in urban ones in the EU-15. In the EU-13,
growth rates of GDP per head between 2008 and 2011 were much lower than in the
preceding period but still positive. Growth in urban regions was slightly higher
than in others. 
Employment declined in all types of region, by
more in urban regions in the EU-15 and in rural regions in the EU-13. Productivity
continued to grow in the EU-15 and, more especially, in the EU-13. In both,
growth was higher in rural regions than elsewhere. 
Table 3: Real
GDP per head, productivity and employment per head growth by urban-rural
typology, 2000-20011
 
In 2011, the differences in GDP per head
between the three types of region in the EU-15 were much smaller than in the
EU-13. In rural regions, average GDP per head was 90% of the EU average, in
urban regions, 124% of the average, a difference of 34 percentage points. In the
EU-13, on the other hand, GDP per head in the rural regions was only 46% of the
EU average, while in urban regions, it was 108% of the average, a difference of
62 percentage points. 

Box on Commuting and functional geographies

The difference between GDP per head in urban
regions and other regions is due in part to commuting which tends to distort
the comparison. People working in an urban region and living in a neighbouring
intermediate or rural region inflate GDP per head in the urban region (by
contributing to its GDP, but not its population) and deflate GDP per head in
the region they live (by adding to its population but not its GDP). In many
cases, this effect is small, but in some cases it can be very large. For
example, half the people working in Brussels live outside the Brussels region,
so that GDP per head in Brussels is around twice what it would be without
commuting. In such a situation, GDP per head is a poor proxy for income per
head.
Using functional regions like labour market
areas[2]
or metropolitan regions avoids this distortion. Of the 272 metropolitan
regions, however, 42 consist of a mixture of urban, intermediate and rural
areas, which means that in these cases, the difference in GDP per head between
the three types of area is likely to be exaggerated because of commuting. 
One way of showing the impact of commuting is
to compare GDP per head (distorted by commuting) with GDP per person employed,
persons employed being measured in terms of their place of work and,
accordingly, not distorted by commuting. GDP per person employed is, of course,
much higher than GDP per head as only about half of the total population is
employed. In a functional region with no inward or outward commuting this
difference would equate to the share of the population in employment. 
However, in the case of the Paris metropolitan
region, for example, GDP per head is much higher than implied by this
difference in the two areas with net inward commuting, while it is
substantially lower higher in the areas with net outward (see figure). This
illustrates the inflation of GDP per head in regions with more jobs than
employed residents and the reduction in regions which have the opposite (which
are, in effect, ‘dormitory’ regions for the region where economic activity is
concentrated). 
There is a growing consensus that economic
policies and development strategies should be related to more functional
regions rather than covering particular parts of an economic area or labour
market. This can be seen in the emergence of new instruments to govern
metropolitan areas in France, the UK and other countries. It is also why when
assessing regional competitiveness several NUTS-2 regions have been combined to
ensure that a single metropolitan area was not divided into multiple regions.
Figure 5 GDP per head and per person employed
in the Paris Metropolitan regions, 2010
 Map 1 Metropolitan regions by type || Map 2 Urban-rural regional typology 
[1]        Parkinson
M. et al. 2012, Second Tier Cities in Europe: In An Age of Austerity
Why Invest Beyond the Capitals? ESPON Study
[2]       Eurostat has created a taskforce to investigate different
labour market methodologies. Results will be available in 2015. 

Box on new
degree of urbanisation and urban-rural typology

Since the 5th Cohesion Report, the
European Commission has developed a new typology of local areas which is linked
to a typology of regions[1].
Both typologies rely on a new analytical tool,
the population grid, which is used to identify three types of cell:
(1)       urban centre (alternative
name: high-density cluster): contiguous grid cells of one square km with a
density of at least 1 500 inhabitants per square km and a minimum
population of 50 000
(2)       urban cluster: contiguous
grid cells of one square km with a density of at least 300 inhabitants per
square km and a minimum population of 5 000; 
(3)       rural grid cell: grid cells
outside urban clusters; 
These are then used to define three types of
municipality (local administrative units level 2) as follows:
(1)       cities: at least 50% of the
population live in an urban centre 
(2)       towns and suburbs: less than
50% of the population live an urban centre, but more than 50% live in an urban
cluster; 
(3)       rural areas: at least 50% of
the population live in rural grid cells.
These cells are also used to define NUTS-3
regions as follows:
(1)       predominantly urban:, less
than 20% of the population live in rural grid cells; 
(2)       intermediate: between 20%
and 50% of the population live in rural grid cells; 
(3)       predominantly rural: at
least 50% of the population live in rural grid cells.
This creates an especially close link between
rural regions and rural areas which are defined in the exact same way.

Box on EU-OECD city and commuting zone definition and metropolitan
regions

The new EU-OECD definition is linked to
metropolitan regions.
The cities in this new definition are identical
to those identified by the degree of urbanisation (see above). A city is
defined as one or more municipalities (local administrative unit level 2) that
have at least 50% of their population living in an urban centre. 
The commuting area of the city is defined as
all contiguous municipalities where at least 15% of the residents in employment
commute to the city. Municipalities below this threshold but surrounded by
municipalities above this threshold are also included in the commuting area.
(For more details, see Dijkstra and Poelman 2012[2]
and OECD 2012[3]).
The city and its commuting zone form a functional urban area.
This report includes data for urban centres
(see access to public transport), cities (see at risk of poverty) and cities
and their commuting zone (see air quality).
The metropolitan regions[4] represent cities plus
commuting zones of more than 250 000 inhabitants. If a NUTS-3 region has
more than 50% of its population living in such a city plus commuting zone, it
is considered as (part of) a metropolitan region.
The typology distinguishes three types of
metropolitan regions:
(1)       capital city regions (i.e.
where the national capital is located);
(2)       second-tier metropolitan
regions;
(3)       smaller metropolitan
regions.
Second-tier metropolitan regions consist of the
largest cities in the country excluding the capital. A natural break in population
size was used to distinguish the second-tier from the smaller metropolitan
regions. 

7.     Start-ups rates and
Entrepreneurship rely on individual initiative and the right institutional
environment

Business demography reflects the dynamism
of an economy through the adaptation of economic structures and entrepreneurs
to evolving market conditions. In the period 2014-2020, Cohesion Policy is focussed
heavily on supporting smart growth with particular emphasis on innovation and
high growth firms, with programmes aimed at supporting the innovative capacity
of SMEs. In previous periods too, a substantial share of Cohesion Policy
funding has been devoted to improving the business environment and supporting
entrepreneurship. 
Regional business demography indicators
show where new businesses are created and how quickly firms grow. In this
section, two main indicators are examined: the birth rate of firm (firms created
in a region relative to the number of firms active there) and the death rate
(firms going out of business which were last active in the region relative to
the total number active). 
The birth rate of enterprises is one of the
main drivers of job creation and economic development. New, innovative
enterprises tend to increase the competitiveness of an economy both directly
and by pushing competitors to become more efficient. Death rates tend to
indicate the economic activities which are no longer profitable. 
In 2010, newly-created enterprises tended
to be more numerous in (or around) capital city regions, both in more developed
and less developed Member States. Birth rates were also high in regions where
the economy continued to expand (in Poland especially) or experienced a quick
recovery after the severe contraction of 2009 (as in Slovakia) (Figure 14).

In France, which on average recorded a high
birth rate of businesses, regional differences are marked, higher rates being
registered in outermost and southern regions as well as around Paris and in the
regions bordering Belgium and Germany. 
In Austria and Italy, the birth rates were
particularly low. . In other countries, there are also large regional
difference, though in some cases this is mainly due to a single region, such as
Ilfov in Romania, the NUTS 3 region surrounding Budapest and Byen København
(with a high rate) and Bornholm (a low rate) in Denmark.
Figure 1 Birth rates of enterprises, 2010
Death rates of enterprises were particularly
high in Romania, Slovakia and in most Polish regions as well as in southern regions
of Spain (e.g. in Andalucia and Murcia), Italy (e.g. Calabria) and the eastern
regions of Denmark. Low death rates were recorded in the Netherlands, Austria, north-east Italy and in several regions in France. Interestingly, regions in Poland and Slovakia tended to record high rates of both births and deaths of enterprises, indicating
a particularly high rate of business turnover, or ‘churn’. In Romania, high death rates were accompanied by low rates of birth in 2010 reflecting the
further contraction of the economy following the severe recession in 2009. 
Figure 2 Death rates of enterprises, 2010
This new set of data on
regional business demography has the potential to become a critical policy
indicator to measure business dynamics at the regional level. It can reveal
where start-up rates are substantially below average or which regions have a
high death rate or a low survival rate. All three should give rise to further
investigation to identify why the business environment in the regions concerned
seems sub-optimal. 
Entrepreneurship is an
important driver of economic development, restructuring and the growth of
regions. Entrepreneurship can be seen as a dynamic, institutionally embedded
interaction between the attitudes, abilities, and aspirations of individuals, shaping
the allocation of resources through the creation of new ventures and the operation
of existing ones. Accordingly, entrepreneurship reflects a complex process involving
individual decision-making and the wider context where this occurs. The phenomenon
has been studied from both the individual and context angles, but the complex
relationship between the two has not been studied before at regional level. 
The Regional
Entrepreneurship and Development Index – REDI
A recent EU-project[5] has developed an index
(REDI - Regional Entrepreneurship and Development Index) that describes the
entrepreneurial process, taking account of both individual attitudes and
characteristics and the regional context and, accordingly, not only whether
people are willing to start a business but also whether the conditions to do so
are in place in the region concerned.
The index is composed of three sub-indices covering entrepreneurial
attitudes, abilities and aspirations. Each of the sub-indexes has an individual
component (relating to the individual decision making behaviour) and an
institutional component (relating to the context). Entrepreneurial attitudes
indicate the attitudes of the population in a region as they relate to entrepreneurship,
including elements such as perception of opportunities and risks, cultural
support and networking. These are measured by indicators of market
agglomeration, social capital and the extent of corruption. Entrepreneurial
abilities measure characteristics of entrepreneurs and business start-ups with
high growth potential, such as the take-up of technology, the level of human
capital and the degree of market competition. The indicators used include the
educational level, the degree of sophistication of businesses and the freedom
for businesses to operate. Entrepreneurial aspirations refer to the
distinctive, strategy-related nature of entrepreneurial activity such as
product and process innovation and access to financing. These are measured by
indicators of innovation, R&D and the development of the financial market.
The indicators can relate to either regions (NUTS1 or NUTS2) or countries.
The variations in
entrepreneurship, as measured, across the 125 regions are substantial (Map 9), with
a difference of over four-fold between the region with the highest ranking
(Hovedstaden in Denmark) and that with the lowest (Macroregiunea doi in Romania). There are four Swedish, two Danish, two British, one French and one Irish region in
the top 10, Hovedstaden being followed by the two regions with the largest
cities in the EU, Greater London and Ile de France. Larger, more developed city
regions with higher GDP per head generally rank higher than less developed
regions in the same country. In most cases, capital city regions are ranked
first in each country. The regions with the lowest scores are in Romania, Hungary and   Greece.
The index contains both
individual-level and institutional or environmental indicators (see box), which
reflect the regional context. For example, a factor such as the perception of
risk is the outcome of combining an institutional factor (the actual business
risk faced by a start-ups as measured by the business closure rate) and an
individual one (the personal acceptance of risk by entrepreneurs, measured by the
proportion of the population aged 18-64 stating that the fear of failure would
not prevent them starting a business).
Analysis of the
individual aspects gives a different picture than the combined index (Map 10). The
top 10 regions of the 'individual' index still include 5 of those in the top 10
of the combined index (e.g. London, Hovedstaden and Ile de France), but there
are also the two Slovenian regions and the two Irish ones. The bottom 10
regions, unlike in the case of the combined index, include three German and
four Polish ones.
This analysis can help
regions tailor their strategies to remove the key bottlenecks to unleash the
potential of entrepreneurship, including social entrepreneurship.
 Map 1 REDI combined index || Map 2 REDI individual dimension 

8.     Innovation remains
spatially concentrated

As widely documented in
the economic literature, research and innovation play a critical role in
determining the economic performance of countries and regions. Innovation,
understood in the broad sense to include product, process, market and
organisational innovation, is identified as one of the major engines of
economic growth, employment and ecological sustainability and accordingly is of critical importance for social progress as well as prosperity. 
In particular, innovation is an important driver of long-run productivity growth
and, as such, is crucial for maintaining the competitiveness of firms over
their rivals. This is particularly true for firms in Europe which more and more
compete with firms located in less developed parts of the world and in emerging
economies. These are not only catching up fast in terms of technology but they
also continue to benefit from lower labour costs due in part to different
standards in the organisation of the labour market, a lack of social protection
for workers and lower income expectations, though low labour costs are offset
to some extent by lower productivity. From this perspective, innovation, as well
as the capacity to assimilate innovation produced elsewhere, can be regarded as
an important condition for maintaining the specific features of the European
social model.
In addition, contrary
to growth obtained from restructuring economies, growth arising from innovation
is in principle without bounds, which is why it is central to securing economic
growth and development in the long-run[6].

One of the main
indicators for assessing investment in innovation is the level of regional
expenditure on research and development (R&D).[7] Technical progress is
to a large extent driven by R&D activities and expenditure on R&D
indicates the effort devoted by the public sector and firms to generating innovations
and new market opportunities.[8]
The role played by R&D in supporting key engines of growth has made it a
headline target objective of the Europe 2020 strategy, specifically that
expenditure on R&D in the EU should reach 3% of GDP by 2020.
According to the latest
data available, expenditure on R&D in the EU-28 amounted to around 2% of
GDP in 2010. However, there is wide variation around the average with some
regions – Braunschweig in Germany and Brabant Wallon in Belgium –having
expenditure on R&D as high as 8% of GDP and others (Ciudad Autónoma de
Ceuta in Spain, Dytiki Makedonia and Notio Aigaio in Greece, and Severozapaden
in Bulgaria) having expenditure of only around 0.1% of GDP.
R&D expenditure in
the Union has steadily increased over the past decade, from 1.8% of EU-27 GDP
in 1995 to 2.0% in 2011. However, the pace of this increase is too slow to
close the gap with other highly developed economies in the world, like Japan where R&D expenditure amounted to 3.7% of GDP in 2011 or the US where it stood at 2.9% of
GDP.
In general, regions
with high expenditure on R&D are the most highly developed ones. Of the 20
regions in the EU with the highest expenditure on R&D, 16 have a level of
GDP per head above 100% of the EU-27 average. The vast majority of regions
recording low levels of expenditure on R&D are located in southern, central
and eastern Member States or are regions with relatively low levels of GDP per
head in the Western Member States.

8.1.    R&D and the 2020 target

Expenditure on R&D in 2011 exceeded the
Europe 2020 target of 3% in only 32 regions in the EU and it was less than 1%
in 100 regions. Expenditure in the majority of regions is far below the
national target, which for most Member States is below the overall target. Only
in 32 regions has expenditure reached the national target and even in Member
States with expenditure close to the national target (e.g. Denmark, Sweden and Germany), regional disparities are still considerable.[9] However, not all
regions can or should try to reach the national target since regional
differences in this regard are an inherent feature of the situation, as noted
below. 
R&D expenditure is generally high in
regions with a large city, though the regions with the largest city, which is
usually the capital, do not in all cases have the highest levels. Indeed, many
regions with high expenditure do not have a very large city, such as Oulu in Finland or Styria in Austria. In part, this is because very large cities tend to
have a smaller share of activity in manufacturing, which generates most
R&D. 
R&D by no means captures all expenditure on
innovation. While it captures a large share of innovation expenditure in
manufacturing, misses most of the expenditure in services. Because
manufacturing is spatially concentrated, it is unrealistic to expect that all
regions can reach the national target for R&D spending. Indeed, due to the
positive ‘externalities’, or spill-overs, from concentration of technological
innovation in a few locations, many regions should not aim to reach their
national R&D target, but should focus instead on other ways to innovate. 
Table 1 Total R&D expenditure and the distance
to the 2020 target, 2011
   || More developed || Transition || Less developed || EU-28 ||   
 RD as % of GDP, 2011 || 2.3 || 1.3 || 0.8 || 2.1 ||   
 distance to national target || 0.4 || 1.4 || 0.9 || 0.9 ||   
 Share of regions* that have reached national target in % || 21 || 8 || 5 || 14 ||   
 * Includes only regions with data and a national target ||   ||   ||   
 Source: Eurostat and DG REGIO calculations ||   ||   ||   ||   
 Map 3: Total expenditure on R&D, 2011 || Map 4 Total expenditure on R&D, distance to national target, 2011 
Innovation is a key factor of development for
all regions in the EU, not only the high-tech ones. However, regions differ
widely in their performance with respect to innovation. Some are close to the
global technology frontier and their growth generally hinges on R&D and
technological innovation shifting this frontier outwards. Other regions are
catching up with the leading ones through a process of absorbing existing
technology and their main challenge is to increase the capacity of workers and
enterprises located there to be able to do this.
For another set of regions, the limiting factor
is their low endowment of infrastructure and the quality of the business
environment. It is therefore important to take account of more aspects of
innovation than simply R&D, or indeed technological innovation, in order to
give a more accurate and complete picture of the geography of innovation in the
EU. This is the approach adopted by the Regional Innovation Scoreboard (RIS) in
assessing performance in this regard in NUTS 1 and 2 regions.
The RIS covers 190 regions in Europe in total –
all those in the EU together with those in Norway and Switzerland[10]. It is based on 11
indicators reflecting various aspects important for innovation, such as ‘Human
resources’, ‘Finance and support’, ‘Firm investment’, and ‘Linkages and
entrepreneurship’ (capturing entrepreneurial efforts and related efforts at
collaboration) as well as ‘Outputs’ (i.e. the number of firms that have
introduced innovations on to the market or within their organisations and their
effects on employment, exports and sales). For purposes of analysis, regions
are grouped into four categories: innovation leaders (34 regions), innovation
followers (57 regions), moderate innovators (68 regions) and modest innovators
(31 regions).
In general, regional performance as measured tends
to be in line with national performance. Most of the regional innovation
leaders and innovation followers are located in countries which are identified
as such in the Innovation Union Scoreboard (IUS) and similarly for the regional
moderate and modest innovators. All the innovation leader regions are located
in just 8 EU Member States (Denmark, Germany, Finland, France, Ireland, Netherlands, Sweden and the UK), indicating that excellence in innovation is concentrated
in relatively few parts of Europe. Regions in Bulgaria, Croatia, Greece, Poland and Romania are assessed as having the worst performance.
There are, however, some variations in regional
performance within countries. In particular, 14 countries have regions in two
performance groups and four (France, Portugal, Slovakia and Spain) have regions in three groups. Only Austria, Belgium, Bulgaria, Czech Republic and Greece have all regions in the same group.
 Map 5 Regional Innovation Scoreboard, 2014 || Map 6 Regional innovation growth performance, 2008-2014 
The analysis conducted for the period 2004-2010
shows that innovation performance has improved in most regions (155 out of 190,
see map). Regions with relatively high rates of improvement are located right
across the EU. At least one region in every country increased its performance
by more than the EU average. This is the case for all regions in Austria, Ireland, Netherlands and Switzerland.
On the other hand, in most countries (14), the
performance of at least one region worsened over the period. The score declined
by over 2.5% a year in 7 Polish regions, 4 Spanish regions and one region in
each of Croatia, Italy and Romania. It declined by even more (by over 10% a
year) in Ciudad Autónoma de Ceuta and Ciudad Autónoma de Melilla in Spain and Podlaskie and Kujawsko-Pomorskie in Poland. Overall, the results indicate that there is no
sign of any catching-up, in the sense of performance in the less innovative
regions converging towards that in the more innovative ones.
Most of the highly innovative regions
(innovation leaders and high performing innovation followers) have high scores
on most indicators (e.g. human resources, R&D expenditure, entrepreneurship
and product and process innovations). By contrast, the majority of the moderate
and modest innovators have widely varying scores for the different aspects. 
A positive attitude of people towards novelty
(as monitored by the European Social Survey) is a key factor for both
entrepreneurship and innovation. In addition, regional performance depends to a
significant extent on a well-developed system of public financial support for
innovation with many companies receiving some form of support. This suggests
that public funding can compensate for a lack of private funding in stimulating
innovation activity.
In general, the analysis confirms the wide
diversity of regions in the EU in terms of innovation performance which
reinforces the notion that innovation has a strong regional dimension. Given
this wide variation, programmes for supporting innovation, including Cohesion
Policy programmes, need to take explicit account of the local or regional
context when devising the kind of support to provide. 

Box on Competitiveness and Innovation
Framework Programme 

The Competitiveness and Innovation Framework
Programme (CIP) is one of the EU funding programmes supporting innovation
activities (including eco-innovation) the EU, access to finance and business
support services. The programme, which had a budget of EUR 3.6 billion in the
2007-2013, is aimed at medium-sized enterprises and cohesion is not an explicit
objective, although the main projects it supports contribute to achieving
Cohesion Policy goals. 
The main means of support for SMEs are
financial instruments (with funding of around EUR 1 billion) though networks,
platforms and agencies (e.g. the Enterprise Europe Network, PRO INNO Europe and
Europe INNOVA) are also provided. Other initiatives are focused on European
Clusters (e.g. European Cluster Observatory, European Cluster Excellence
Initiative) and on supporting eco-innovation, market replication projects and
ICT related pilot projects. 
The CIP also supports statistical analysis of
regional innovation. The Regional Innovation Monitor Plus (RIM Plus) project
provides a platform for sharing knowledge of innovation policy trends in EU
regions. The Regional Innovation Scoreboard (RIS) provides a comparative
assessment of how European regions perform with regard to innovation. The 2012
edition of the RIS confirms that there is considerable diversity in regional
innovation performance and that differences do not change much over time. Between
2007 and 2011, therefore, only a small number of regions improved their
performance.
Building on the lessons learnt from the CIP,
two programmes will provide support for competitiveness and innovation in the
2014-2020 programming period. The Programme for the Competitiveness of
Enterprises and SMEs (COSME) will focus on competitiveness issues of particular
relevance for SMEs. Innovation will be covered by the Horizon 2020 Framework
Programme for Research and Innovation. Improving synergies between COSME,
Horizon 2020 and the Structural Funds is a key element of the new programmes.
Regions are required to establish smart specialisation strategies at regional
level in order to enhance the impact of their investment, to take better
advantage of the innovative and creative potential of the Internal Market and
to relate their strengths in research and innovation to business needs. In this
context, Cohesion Policy funding can be an important source of support for the
deployment of advanced manufacturing, modernisation of factories and the
development of key enabling technologies.

Box on Research Framework Programmes 

Research Framework Programmes are the main
means of providing support for research and innovation across the EU. They primary
objectives are to strengthen the EU’s scientific and technological base and its
international competitiveness through research cooperation with partners in
other countries.
The 7th Research Framework Programme (FP7) with a budget of some EUR 50 billion for 2007-2013was aimed at making
the EU the leading research area in the world by supporting research excellence
wherever it took place. 
Support was provided for a range of activities
such as encouraging greater involvement of SMEs in research activities;
supporting the creation of large-scale, pan-European research infrastructure[11] and the optimal use of
existing facilities and equipment. The concern was also to strengthen the
R&D potential of regions by encouraging the emergence of research clusters
(involving the triple helix of researchers, businesses and the public
authorities) through the Regions of Knowledge initiative and by supporting
research centres of excellence in Convergence regions through the Research
Potential initiative.
                     Horizon 2020, the EU's new programme for
research and innovation, will run from 2014 to 2020
with a budget of nearly EUR 80 billion (at current prices), supplemented by the
private investment that it is expected to attract. Its intention is to link
research and innovation by supporting scientific excellence, industrial
leadership and measures to tackle social challenges. The goal is to help produce
world-class science in the EU, remove barriers to innovation and make it easier
for public and private sectors to work together in producing innovation. 
Horizon 2020 brings
together all EU-level funding for research and innovation in a single
programme, covering the current 7th Framework Programme, the innovation
activities of the Competitiveness and Innovation Framework Programme and the
European Institute of Innovation and Technology. The intention is provide seamless
funding for innovative projects from the laboratory to commercial exploitation
and to bring together previously separate activities to better tackle societal
challenges as regards health, clean energy and transport.
All forms of
innovation are covered, including in services and social innovation and support
is also given for developing the market for innovations and for devising
relevant legislation on public procurement, standard setting and so on.
The aim is to
attract the best researchers regardless of where they are located, and funding will continue to be allocated on the basis of competitive calls for
proposals without taking account of the regions from which the proposals come. Such an approach,
however, needs to be complemented with measures to ensure that funding is open
to a wide range of applicants, especially in the less developed regions. Support
will, therefore, be provided to regions under Cohesion Policy to help them
develop their capacity for research and innovation.
As in the
previous programming period, some of the research funded will be on regional
issues. Research in Socio-economic Sciences and Humanities, with a budget of
EUR 623 million for 2007–2013, therefore, included studies of regional
performance, smart specialisation, social innovation, urban problems and rural regions under pressure
from globalisation as well as of social cohesion in cities. Horizon 2020 will
continue to support studies of these kinds under ‘Societal Challenges’, as well
as research into innovative spatial and urban planning to create sustainable
and inclusive environments.

8.2.    Patenting in the EU and the USA

Over the two
years 2008-2009, some 135 patent applications per million people were made to
the European Patent Office (EPO). In the US, there were 408 applications per
million over the same period. The higher patent rate in the US reflects a more innovative economy,
though also a greater tendency to apply for patents.
Although there are
marked variations across regions in both the EU and US, most US States have a
much larger number of patents per head than EU regions. In the EU, the regions
with the highest patent
application rates are Noord-Brabant (559 per million people), Stuttgart (544) and
Mittelfranken (505); other regions with relatively high rates are in Germany, southern England, Sweden and Finland. The majority of the EU regions, however, have a relatively
small number of patents per head. 
In US, the States
with most patent applications are situated on the East and West Coasts, in  Massachusetts (879 per million people) and California (864) especially.
The patent
application figures suggest
that whereas some regions in the EU may be close to the global knowledge
frontier in certain areas of economic activity, most regions are not. In the US, there seem to be more States which fall into the former category.
 Map 7 Patent applications to the EPO, 2008-2009 || Map 8 US, patent applications, 2011-2012 
 Map 9 Population aged 25-64 with tertiary educational attainment level, 2013 || Map 10 Population aged 25-64 with low educational attainment level, 2013 || 

9.     Tertiary educational
attainment is increasing, but large disparities persist

Tertiary education, with its links to
research and innovation, can help to provide the highly skilled human capital
that the EU needs to create jobs, economic growth and improvements in social
welfare[12].

A well-educated workforce is key to
prosperity. There tends to be a strong correlation between the educational
attainment of a region’s workforce and median earnings in the region. In
addition, attaining a relatively high education level tends to mean less risk
of being unemployed. The share of people aged 25-64 with a high educational
attainment level (i.e. with tertiary qualifications), however, varies significantly
across regions (Map 17). In only 10% of the regions in 2013 was the share
over 40%, with Inner London, Brabant Wallon and Helsinki having the highest
figures. In most cases, regions with capital city cities or adjoining them have
the highest educational attainment levels[13].
By contrast, the share was less than 15% in
15 regions, mainly located in Italy and  Romania. 
Regional variations can be substantial
within a country. In the UK, the share of people with tertiary education varies
between 28% and 63%, more than the variation between Member States, which is
only between 16% and 42%. At the other extreme, around a quarter of people aged
25-64 in the EU have only basic schooling (i.e. less than upper secondary level
qualifications) Many of the regions where the proportion of people with this
level of education is largest are in the southern Member States, in a number of
cases, the figures exceeding 50% (Map 18). 
In most cases, regional extremes seem to
follow national averages (Figure 14), but there are a few exemptions. For
example, Romania has a higher share of low-educated than the UK or Denmark, but Bucureşti – Ilfov has a lower share than any of the regions in these two Member
States. 
Figure 3 Tertiary educational attainment country and
regional extremes, 2013 
Source Eurostat
Figure 4 Low education rates by country and regional
extremes, 2013
The tertiary
educated and the 2020 target 
The Europe 2020 strategy is aimed at increasing
the share of the population aged 30-34 with tertiary education to 40% by 2020.
Member States have set national targets for this varying from 26% (in Italy) to 60% (in Ireland). In the EU-27, the share increased significantly between 2008 and 2012
from 31% to 36%, suggesting that the Union-wide target of 40% should be
achievable without much difficulty. 
The prevailing situation in 2013, however,
varies markedly between regions (Map 19 – because of the relatively small
sample size on which the data are based, a three-year average is used for
regions to ensure more reliable figures). 
Table 2 Population aged 30-34 with a tertiary
education, average 2013
   || More developed || Transition || Less developed || EU-28 
 Population aged 30-34 with tertiary education, 2013 || 41.3 || 32.3 || 28.9 || 36.8 
 Change 2008 - 2013, in pp || 5.7 || 1.1 || 8.1 || 5.8 
 Change 2000 - 2008, in pp || 9.3 || 9.1 || 8.5 || 8.6 
 Distance to national target || 1.0 || 12.2 || 8.7 || 4.3 
 Share of regions* that have reached national target, in % || 27 || 0 || 6 || 17 
 * Includes only regions with data and a national target ||   ||   
While 29% of the 124 more developed regions
with data and a national target have already achieved the latter, not a single
transition region and only four of the less developed regions have reached
their national target. 
Regions with less than 20% of the population
aged 30-34 with a tertiary degree are located in Italy, Romania, Greece,
Slovakia, Czech Republic, Greece and Hungary. The average distance to the
national target was reduced by 9 percentage points in all three categories of
regions between 2000 and 2008. Between 2008 and 2013, the distance narrowed most
in the less developed regions by 8 percentage points, followed by the more
developed regions (5.7 percentage points). In the transition regions, the
distance to the national target did not narrow substantially between 2008 and
2013 when it was still 12 percentage points as compared with only 1 percentage
points for the more developed region and 9 percentage points for the less
developed ones. This implies that, on present trends, the targets are likely to
be reached in more and less developed regions, but that more needs to be done
in transition regions to reach the target.
[1]       http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Urban-rural_typology

[2]           Dijkstra L. and Poelman H. 2012, Cities
in Europe, the new OECD-EC definition, Regional Focus RF 01/2012, DG REGIO.
[3]        OECD,
2012, Redefining urban: a new way to measure metropolitan areas, www.oecd.org/gov/regional/measuringurban
[4]       http://epp.eurostat.ec.europa.eu/portal/page/portal/region_cities/metropolitan_regions

[5]        Szerb
L., J. Acs Z., Autio E., Ortega-Argiles R., Komlosi E., 2013, REDI:The
Regional Entrepreneurship and Development Index – Measuring regional
entrepreneurship, Final report, 2013, Research financed by the European
Commission Directorate-General Regional and Urban Policy
[6]       The importance is recognised by the Innovation Union
Initiative launched in 2010 as part of the Europe 2020 strategy which is aimed
at boosting research and innovation throughout the EU through 34 action points.
[7]       It should be noted however that if R&D expenditure is
likely to underestimate innovation activities, particularly in sectors outside
manufacturing where non-technological innovation is frequent (see the section
on the Regional Innovation Scoreboard below). 
[8]       Note that R&D expenditure is an input measure which does
not capture the extent to which this expenditure is actually transformed into
innovations and, more specifically, commercial innovations. 
[9]       See ESPON (2013), Territorial Dimension of the Europe 2020
Strategy, ESPON Atlas.
[10]     Details about the method and the indicators used to establish
the RIS can be found in the report prepared for the European Commission 'Regional
Innovation Scoreboard 2014', European Commission, 2014. 
[11]     European Strategy Forum for Research Infrastructures.
http://cordis.europa.eu/esfri/roadmap.htm 
[12]       European
Commission, 2012, Education and training monitor 2012, Publications
Office of the European Union, 2012, ISBN 978-92-9201-350-9, doi: 10.2797/51172
[13]       It should be noted, however, that the very different ways in
which education systems are organised across the EU, such as, for example, the
much longer training than elsewhere generally required of skilled manual
workers in Germany or Austria outside of the university system and who acquire
a high level of skills as a result, means that the number of people with
tertiary education is not necessarily a reliable indicator of a highly-skilled,
workforce, or even a well-educated one.
 Map 1 Population aged 30-34 with a tertiary educational attainment, 2011-13 || Map 2 Population aged 30-34 with high educational attainment 2011-13 Distance to national 2020 target 

10.   Gaps in the digital and
transport networks are being filled, but more remains to be done
10.1.  Digital networks are spreading, but unevenly

Access to high
capacity telecommunication networks is a key factor of competitiveness and
economic growth. The provision of digital services and the capacity to operate
successfully in a global business environment increasingly rely on fast and
effective broadband connections. ICT infrastructure is therefore a major
determinant of the development potential of EU regions. The most prosperous
regions are in general already well-endowed in this regard, though there are
still serious gaps in many of the less prosperous ones.  
The extent of
broadband coverage has increased significantly in the EU in recent years. In
2012, 96% of households in theEU-27 had access to at least one fixed broadband
network[1],
while, as regards wireless technologies, High Speed Packet Access (HSPA) is
available to 95% of them and there is full coverage of high capacity KA-band
satellite broadband in all but four Member States (Estonia,
Latvia, Lithuania and Sweden). However, coverage is
much higher than take-up and in 2012 only around 70% of households with access
(67% of the total) had a fixed broadband subscription.
Disparities are also pronounced between regions, especially urban
and rural ones. In 2012, 9.1 million homes in the EU still did not have fixed
broadband coverage and over 90% of these were in rural areas. Coverage was
below 40% in such areas in Poland and Bulgaria. Coverage is almost complete in
most urban areas and cities, though there are a number of areas with a coverage
of below 90%, most of them in northern parts of Sweden and Finland and in
southern and Eastern Europe, and a few where it is below 75%, all of them in
Poland. 
The gap is much wider for Next Generation Access[2] (NGA) (figure 16). In
2011, 78% of rural households in the EU had access to standard broadband but
only 12% to NGA. Contrary to the situation for standard broadband, regions
lagging behind are mostly located in the EU15 Member States. While coverage is
at or near 100% in the Netherlands, Belgium and Malta, it is below 40% in France, Ireland, Italy, Greece, Poland and Cyprus. There is no access to NGA for homes in rural
areas in Luxemburg,, Ireland, Italy, Cyprus, Slovakia, Latvia and Poland and only marginal coverage in Germany. 
Figure
1: NGA broadband coverage, 2012
(% of rural and urban population with NGA)
Household take-up of broadband has increased significantly in recent
years along with coverage. While in 2009, only around 56% of households in the
EU had a broadband subscription, the figure was more than 76% in 2013. However,
large differences remain between regions (see Map 21). In Severozapaden (Bulgaria), Kentriki Ellada, Nisia Aigaiou Kriti (Greece) and Nord-Est (Romania), the take-up rate
was below 50% in 2013 while in Flevoland, Utrecht (Netherlands), London, South West (UK), Helsinki-Uusimaa (Finland) and Bremen, it was over 90%. 
The same picture emerges for businesses. Between 2010 and 2013, the
proportion of companies with 10 or more persons employed in the EU-28 with a
broadband subscription increased from 84% to 90%. In Finland, France and Denmark, the take-up rate was over 96%. By contrast, the take up rate was just below 80%
in Bulgaria, Greece, Croatia and Poland and only 61% in Romania.

Box on the digital agenda

ICT is estimated to have accounted for half of
productivity growth in the EU in the first decade of the present century[3]. Development of ICT
networks is, therefore, important for economic cohesion in the Union as less developed regions tend to lag behind in broadband access. The goals of the
digital agenda for 2020 are (1) that the entire EU population should be covered
by fast broadband (over 30 Mbps), (2) that at least half the EU population use
broadband with a speed of 100 Mbps or more and (3) to double public investment
in ICT R&D. 
Map 3: Households with a broadband connection,
2013

10.2.  Road network in central and eastern member states still
considerably less developed

In 1955, only a few links of the TEN-T core road network allowed
people to travel at an average speed of over 80km per hour (see map). The vast
majority of links had an average speed of below 70 km an hour. In 1970, the
situation had improved substantially with many links in Germany, Italy, the Benelux and the UK having average speeds of over 80 km per hour though few or
none at all in the rest of the EU, including in the central and eastern
countries. 
The gap between the north-west of Europe plus Italy and the rest had widened further by 1980, with many links in the former having an
average speed of over 90 km per hour. Portugal, Greece and the central and
eastern Member States did not have a single link with an average speed of over
80 km per hour and some had speeds of below 60. In Spain, the only link with a
speed of over 80 km per hour was Valencia to Barcelona. 
By 1990, average speeds increased further but the gaps between
countries remained. By 2000, the average speed in Greece, Spain and Portugal had risen substantially, on some links reaching over 100 km per hour. By 2012,
speeds on the links in Spain and Portugal had caught up with those in the
highly developed Member States. These improvements in the speed of the main
road network in these three countries have been largely financed by Cohesion
Policy. 
Speeds on the links in Poland, the Baltic States, Romania and Bulgaria, however, remained slow compared to the rest of the EU. The full implementation
of the TEN‑T core road network by 2030 would increase the average speeds
significantly particularly in the central and eastern Member States. Both
Cohesion Policy funding and the new Connecting Europe Facility are targeted at
the implementation of the multimodal TEN-T core network.
Map 4: Travel speed on the core TEN-T road
network, 1955-2030
Source: (Stelder et al, 2013), JRC IPTS and REGIO calculations
[1]       See COMMUNICATIONS COMMITTEE, 2012, Broadband lines in the
EU: situation at 1 July 2012 (https://ec.europa.eu/digital-agenda/sites/digital-agenda/files/COCOM%20Broadband%20July%202012%20final_0.pdf).

[2]       Next Generation Access Networks is wired access networks
which consist wholly or in part of optical elements and which are capable of
delivering broadband access services with enhanced characteristics (such as
higher throughput) as compared to those provided over already existing copper
networks.
[3]
      See European digital report, 2010

Box: Common
transport policy contributes to cohesion and regional development, by improving
accessibility

A fully integrated Single Market is not
possible without good connections between the various parts. However,
connections which cross national borders are still lacking in many cases,
especially in the central and eastern Member States, dividing the centre of the
EU from the periphery and hampering the further development of intra-EU trade. 
The Common Transport Policy is aimed at
developing affordable, competitive and energy-efficient modes of transport that
can help to reduce the peripheral nature of regions located far from the centre
of the EU, as well as the development of lagging regions with poor endowment of
transport networks and high transport costs. It includes the development of
Short-Sea Shipping, ‘Motorways of the Sea’, Inland waterways and the more
efficient use of existing railways.
The TEN-T[1]
consists of two layers: a core network to be completed by 2030 and a
comprehensive network feeding into the core network, to be completed by 2050.
The core network will provide essential support for the single market by
facilitating the flow of goods and people around the EU, including in the less
developed Member States (see map). It involves connecting 94 main European
ports to rail and road links, 38 key airports with rail connections into major
cities, 15.000 km of railway lines upgraded to high speed and 35 cross-border
projects to reduce bottlenecks.
A new financing instrument, the Connecting Europe
Facility[2]
(CEF) will support the implementation of the TEN-T, by tripling the budget for
transport infrastructure in the 2014–2020 period to EUR 26 billion, which will
serve as ’seed capital’ to stimulate further investment by Member States. 
Experience shows that TEN-T infrastructure
funding tends to have a strong leverage effect. For the next programming
period, every EUR 1 million of EU funding is expected to generate around EUR 5
million from national governments or, if innovative financial instruments are
used, up to EUR 20 million from the private sector. 

10.3.  Low speeds and low frequencies of trains in central and
eastern member states limit their appeal compared to the car.

Since the 1970s, the share of passenger km travelled by train has declined
as more and more people have switched to using cars. In two areas, however,
rail offers an attractive as well as more resource-efficient alternative to car
or air travel: medium-distance journeys and commuting to work. Conventional
railways can shorten door-to-door journey times of up to 350 km as compared to
air travel and high-speed rail is faster for journeys up to 800 km.
The high-speed rail network (HSL) has expanded continuously. Between
1990 and 2009, lines on which speeds can exceed 250 km per hour increased from
1,000 km to 6,000 km. Over this period, passenger km travelled on these lines
increased from less than 20 billion a year to almost 100 billion[3]. By 2030, if completed,
the planned high-speed TEN-T would extend to over 30,000 km.
There are major differences between regions, however, in the extent
of both high-speed rail networks and conventional ones. In Belgium, France, Spain, Germany, Italy and the UK, large sections of the conventional rail network
have been upgraded for use by high-speed trains together with new high-speed
rail lines being constructed (Map). 
France, Belgium, Sweden and Finland have the most km of railway lines per head of population with trains operating at
speeds of over 120 km per hour. A large number of these were financed with the
support of the ERDF, the Cohesion Fund, the TEN–T allocations and grants from
the EIB.
Despite the significant investment in the modernisation of the rail
network, there are still regional networks where train speeds are less than 120
km per hour. These are mainly in the Baltic States, Poland, Hungary, Romania, and Bulgaria (see Map). Moreover, in few areas, such as central Poland, speeds have fallen since 1990 (Maps …and figure…).
The ability of railways to offer an attractive alternative to travel
by car depends not only on the speed but also the frequency of trains. The
average number of trains per day on rail routes in almost all the regions in
the Baltic States, Poland and Ireland was less than 25 in 2010 (See map), or
less than one an hour each way. With such low frequencies, most people who can
afford to use a car will do so. In contrast, in Netherlands and Denmark, the
average number of trains per day on the TEN-T core lines was 130 or more, which means much less waiting time, better
connections and overall a more attractive offer.
The TEN-T Guidelines set out the aim of having a true EU-wide
multimodal network, including railways, by building new infrastructure but also
by improving existing infrastructure. The importance attached to sustainable
and cleaner modes of transport, such as rail, is reflected in the aims of the Connecting
Europe Facility and in the Cohesion Fund priorities for investment in transport.
Figure 1 - Railway length
per capita with trains operating over 120 km/h, 2013
Figure 2– Change in Railway
length per capita with trains operating over 120 km/h, 1990-2013
 Map 1 Highest speed on railway network, 1990 || Map 2 Highest speed on railway network, 2013 
 Map 3 Passenger trains on TEN-T railway network, 2010 || Map 4 Access to passenger flights, 2011 
Access to passenger flights is greatest close to the major airports
of London, Paris, Frankfurt and Amsterdam  (at over 2000 flights a day) (see Map).
In the EU-15, virtually all regions have access to more than 10 flights a day
within a 90 minute drive. This is not the case in Romania, Bulgaria, Poland, Estonia and Latvia, in part because the road network is of low standard, but also
because of the limited demand for flights in and to some of the regions. 

11.   Trade and foreign direct
investment stimulate growth in the EU-12

Although Cohesion
Policy was created in part because of concern about the impact of the single
market on less developed regions, the integration of the central and eastern countries
has generated a strong growth of trade with the EU15 as well as between
themselves. In 2004, imports from, and exports to, the EU-27 both amounted to
around 20% on average of the GDP of these countries. This figure has risen
substantially since, with a small dip in 2008 and 2009 due to the crisis. In
2012, these import and export flows both represented 40% of their GDP, a
doubling in 8 years. This rapid integration into the single market has enabled
these economies to specialise and become more productive leading to higher
growth rates in both the countries concerned and the EU as whole.
Figure
3 Trade between EU-12 and EU-27, 2004-2012
Foreign direct
investment (FDI) has also provided an important boost to the EU-12 economies.
Most of this has come from other Member States. The crisis, however, has
reduced investment flows markedly. In 2007, the EU-12 received 55 billion EUR
from FDI; in 2009 this had fallen to 23 billion EUR. Since then flows have
increased to around 30 billion EUR in 2012, but are still much smaller even
than in 2005.
Figure
4 FDI in the EU-12, 2005-2012
In all EU-15 and EU-12 Member States, the
capital city region has a relatively large, often the largest, share of
employment in foreign firms. Its greater accessibility, the concentration of
head offices of large companies there and the good links to the national market
tend to attract firms in business services especially. 
Regions close to internal EU borders tend
also to have a larger share of employment in foreign firms than others (see Map).
This is especially the case for manufacturing companies for which proximity to
the rest of the EU internal market is likely to be important. 
Many in southern Italy, southern Spain, northern Portugal, eastern Poland and eastern Hungary as well as most Greek regions have a
relatively small share of employment in foreign firms. Although these regions
tend to be some distance away from the largest part of the single market, which
is a possible explanation, this has not prevented equally distant regions in
Ireland, the Nordic countries and the Baltic States to have much larger shares
of employment in foreign firms. 
Map 5 Employment in foreign firms, 2010

12.   Regional competitiveness
produces limited regional spill-overs in EU‑13

The Regional Competitiveness Index (RCI) is
designed to capture the different dimensions of competitiveness at the regional
level. It is based on 73 mostly regional indicators that are relevant for
competitiveness (Annoni et al 2013[4]).

There are eleven ‘pillars’ which are
grouped into three sets. 
·   The basic pillars: (1)
the Quality of Institutions, (2) Macro-economic Stability, (3) Infrastructure,
(4) Health and (5) Quality of Primary and Secondary Education. These pillars
are most important for less developed regions.
·   The efficiency pillars:
(6) Higher Education and Lifelong Learning (7) Labour Market Efficiency and (8)
Market Size. These are important for all regions.
·   The innovation pillars:
(9) Technological Readiness, (10) Business Sophistication and (11) Innovation.
These are important for intermediate and especially for highly developed
regions. 
To take account of the level of development
of a region, the weights for each set depend on the GDP per head of the region
(Table 23).
Figure 5: Weights used in the regional
competitiveness index 2013
 GDP per head (PPS) 2009 in (EU-28=100) || Basic || Efficiency || Innovation || Total 
 <50 || 35.00 || 50 || 15.00 || 100 
 50-75 || 31.25 || 50 || 18.75 || 100 
 75-90 || 27.50 || 50 || 22.50 || 100 
 90-110 || 23.75 || 50 || 26.25 || 100 
 >110 || 20.00 || 50 || 30.00 || 100 
The index is applied to a modified set of
NUTS-2 regions to try to avoid functional economic areas being divided across
multiple regions. NUTS-2 regions have been combined for the functional economic
areas of London, Brussels, Amsterdam, Vienna, Prague and Berlin. 
The index provides an assessment of where
competitiveness varies substantially within a country. It reveals that
competitiveness has a strong regional dimension, which is important because
many of the factors of competitiveness are influenced by regional and local authorities.

The index can also be a useful tool for EU Member
States with large variations in regional competitiveness to consider to what
extent this is harmful for their national competitiveness and whether it can be
reduced, possibly with the support of Cohesion Policy. For example, the gap
between the capital city region and the second most competitive region in Romania, Slovakia and France is very wide, while competitiveness in Germany does not differ markedly
between regions. 
The lack of regional spill-overs, in
particular around the capital cities of some of the less developed Member
States, was already noted in the 2010 edition of RCI., The 2013 edition
confirms that being close to a competitive region in developed countries tends
to improve the competitiveness of a region, but this is not the case in less
developed Member States. The overall competitiveness of a country depends on
the performance of all its regions and not just on that of the capital city
region. Improving the business environment, providing an efficient transport
network and good access to broadband in other regions might help to reduce the
gaps in competitiveness. 
The index reveals substantial differences
in competitiveness in many countries (see figure). In France, Spain, the UK, Slovakia, Romania, Sweden and Greece, the variation across regions is
particularly large with the capital city region almost always being the most
competitive. In Italy and Germany, however, the capital city region is not the
most competitive. 
Figure 6 - Regional competitiveness index, 2013
Earlier territorial research highlighted
the existence of what was called the ‘blue banana’, an area extending from
greater London all the way to Lombardy passing through the Benelux countries and
Bavaria, as well as a pentagon formed by London, Paris, Milan, Munich and
Hamburg. These areas were seen as having the highest concentrations of economic
activity. This line of research emphasised a strong core-periphery pattern of
economic activity in Europe. 
The RCI, however, shows a more polycentric
pattern with strong capital city and metropolitan regions in many parts of the
EU. For example, Stockholm, Copenhagen, Helsinki, Berlin, Prague, Bratislava
and Madrid, which fall outside the areas distinguished above, all have a high
level of competitiveness (see map). The RCI also shows that, in some countries,
all regions have a high level of competitiveness, while in others, it is only
the capital city region.
Eight out of the top-ten regions in 2010 were
also in the top 10 in 2013. The most competitive region in both years is
Utrecht in the Netherlands, while the London functional economic area and
Berkshire, Buckinghamshire and Oxfordshire in the UK, the Amsterdam functional
economic area and Zuid-Holland also in the Netherlands, Hovedstaden (which
includes Copenhagen) in Denmark, Stockholm and Île de France (the Paris region)
were in the top ten in both years too.
Cohesion Policy has helped to improve the
competitiveness of many regions through for example, investment in innovation,
education, health, accessibility and IT.
Map 6: Regional
Competitiveness index, 2013

13.   Conclusion

Cohesion Policy plays a key role in boosting
smart growth in EU regions, especially in lagging ones. Smart growth is needed
to compete in the global market. The co-financing of investment in innovation
and support of SMEs can improve the competitiveness of the EU and its regions.
The investment in transport, energy and digital networks helps to make the single
market run more smoothly. It has facilitated an increase in trade between the
EU-15 and EU-12 and stimulated foreign direct investment in the latter.
This chapter has shown the extent to which
less developed parts of the EU have been able to catch-up with the rest in
terms of GDP per head and indicated the factors responsible for this. Although
regional disparities were tending to narrow in the years leading up to the
global recession, this and the prolonged crisis which followed put an end to
the process of convergence with rapid increases in unemployment in most regions
but in the weaker ones especially.
The crisis has tended to hit the rural
regions harder than others, with reductions in employment in the EU-15 being
moderated by reductions in productivity but not in the EU-13 where losses in
employment have been larger than elsewhere. On average, metropolitan regions
have resisted the crisis better than others, particularly capital city regions
in the EU-15.
The crisis affected construction and manufacturing
in particular, with both employment and GVA in the former declining
substantially. While employment has also declined in manufacturing, GVA
increased between 2008 and 2013 in the less developed Member States. 
Innovation has increased, but it remains
spatially concentrated. Given the positive externalities of concentrating
technological innovation in particular places, this is in many ways desirable.
Nevertheless, innovation, broadly defined to include the take-up and adaptation
of new technology and know-how developed elsewhere, remains crucial to
stimulating growth in all regions. 
The proportion of population with tertiary
education has risen significantly over time and the Europe 2020 target of 40%
of those aged 30-34 having this level of education is likely to be reached, yet
significant disparities remain across regions. The proportion of people
participating in lifelong learning, however, is well below the target,
especially in central and eastern EU regions.
The gaps in the digital and transport
networks are being filled. Broadband availability is close to 100% in nearly
all regions, but access to the next generation of links to the internet is
largely limited to the most urbanised areas. Southern Member States have
invested heavily in road, rail and air transport over the past 25 years or so,
with substantial support from the ERDF and Cohesion Fund, and now have networks
on a par with those in the more developed Member States. In central and eastern
countries, however, more remains to be done to improve both the rail and road
network, which will also help to make the airports there more accessible. 
Trade and foreign direct investment,
although affected by the crisis, have made a substantial contribution to growth
in the EU-12 underlining the benefits of joining the single market. 
The regional competitiveness index, which
attempts to synthesise all this information, shows that regions in the EU-15
with a large city, usually, but not always, the capital, have the highest
levels of competitiveness and that proximity to such a region tends to boost
the competitiveness of others. In the EU-13, on the hand, the region in which
the capital city is located is always the most competitive but this has not (as
yet) boosted the competitiveness of neighbouring regions. As these countries
develop, and the economic and transport connections between the capital and the
other regions become stronger, spill-over effects are likely to emerge with
growth spreading out to other regions and reducing the gap with the capital
city region.
Although Cohesion Policy has helped the EU
and its region to promote smart growth, many more challenges lie ahead with
several decades of investment necessary to complete the single market and the
core trans-European networks and reduce large economic disparities between
regions.
[1]       Regulation of the European Parliament and of the Council on
Union Guidelines for the development of the trans-European transport network,
entered into force on 1 January 2014
[2]       The Regulation of the European Parliament and of the Council
establishing the Connecting Europe Facility also entered into force on 1
January 2014.
[3]       European Commission, 2009, European high-speed rail — An
easy way to connect (http://ec.europa.eu/transport/wcm/infrastructure/studies/2009_03_06_eu_high_speed_rail.pdf
).
[4] Annoni
P. and Dijkstra L., 2013, EU Regional Competitiveness Index, RCI 2013,
JRC Scientific and Policy reports, Publications Office of the European Union,
2013 ISBN 978-92-79-32370-6, , doi: 10.2788/61698
Chapter 2: Inclusive growth

1.     Introduction

With the introduction of the Europe 2020
strategy, the European Commission strengthened its pursuit of social goals
under the heading of ‘inclusive growth’, which means growth that increases
employment rates and reduces poverty and social exclusion. As the crisis has
gone on, the employment rate has declined further and unemployment and poverty
have increased, making it more difficult to reach the targets set. 
Poverty and social exclusion are
concentrated in different types of area across the EU. In less developed Member
States, they tend to be higher in rural areas, while in more developed ones,
they are typically higher in cities. This latter concentration of the poor and
the deprived in cities where employment opportunities also tend to be
concentrated, is often called the urban paradox and it has not been altered by
the crisis. The crisis has, however, increased poverty and exclusion in
two-thirds of Member States since 2008. 
The highly uneven spatial distribution of
employment opportunities and income in the EU has led to people moving both
between regions within countries and between countries. This has meant that
some regions have seen their population shrink continuously over many decades.
In many of the less developed Member States, internal movements of population
tend to be from rural regions to urban ones, in part to escape the relatively
high poverty rates in the former. The EU also continues to attract migrants
from outside the EU, but in some Member States they find it difficult to
integrate into the labour market. Disparities in health seem to add to the
shift of population within and between Member States. 
Tackling issues related to inclusive growth
is at the heart of Cohesion Policy. Social cohesion was an objective from the
very beginning in the Treaty of Rome, the European Social Fund being created in
1958 to help further this. It is a key dimension of a policy which, even though
it is often targeted at regions, is in the end intended to improve the
well-being of people throughout the EU. 
Accordingly, a significant part of the financial
resources allocated to Cohesion Policy is used to support such initiatives as
training and education, active labour market policies and combating poverty and
social exclusion of disadvantaged groups. Such measures are complementary to
those implemented in other policy areas and are important for the success of
these. For example, support to R&D and innovation cannot be successful if
at the same time human capital is not improved. The social dimension is therefore
a central part of Cohesion Policy and no less important than the economic
dimension in fostering development.

2.     Crisis
wipes out most employment gains since 2000 

This section describes how progress in reducing
unemployment and increasing employment rates suffered a severe blow as a result
of the crisis. It also considers what is required to meet the Europe 2020
targets for early school leavers and life-long learning. 

2.1.    Employment rates declined rapidly
in the regions most affected the crisis

Between 2000 and 2008, the employment rate of
those aged 20-64 in the EU increased on average by 4 percentage points (Table 8).
The crisis, however, has wiped out half the gains made over this period. The
experience over the two periods in the three categories of region under
Cohesion Policy, however, was not the same. In less developed regions, the
average employment rate in 2013 was below that in 2000 because the crisis wiped
out all the previous gains. The Transition regions lost two-thirds of the previous
gain, while the more developed regions lost only a third. 
The crisis has, therefore, tended to widen
disparities in employment rates and in 2013, rates were 11 percentage points
higher in more developed regions than in less developed ones (72% and 61%).
Under the Europe 2020 strategy, Member States have set national targets for the
employment rate which are broadly consistent with the 75% overall target being
achieved by 2020, These vary from 62.9% in Malta to 80% in Denmark and Sweden.
Not all regions within countries are expected to reach the national target as
they start from very different positions. Nevertheless, in the less developed
regions and the Transition ones, employment rates are much further from the
national targets: 9-10 percentage points as against 3 percentage points for
more developed regions. 
Table
1 Employment rate of those aged
20-64, 2000 - 2013 
and distance to national target
   || More developed || Transition || Less developed || EU-28 
 Employment rate population aged 20-64, 2013 || 72.0 || 65.1 || 61.1 || 68.3 
 Change 2008 - 2013, in pp || -1.4 || -2.9 || -2.7 || -1.9 
 Change 2000 - 2008, in pp || 4.1 || 4.6 || 2.4 || 3.7 
 Distance to national target || 3.2 || 9.3 || 10.5 || 6.7 
 % of regions* that have reached national target || 34.6 || 15.4 || 1.4 || 21.7 
 * Includes only regions with a national target ||   ||   
Source Eurostat and
REGIO calculations
Only one in five regions across the EU has
reached their national target and all but one of these are more developed or
Transition regions. The 10 regions where the gap to the national target is
widest are in Southern Spain and Southern Italy together with the French
outermost regions of Reunion and Guyane (Map 10).
Significant differences in employment rates
between regions are common to most countries, underlining the regional nature
of labour markets, rates being less than 60% in many regions in Greece, Croatia,
southern Spain and southern Italy as well as some regions in Bulgaria, Romania
and Hungary (Map 9).
 Map 1 Employment rate, (ages 20-64), 2013 || Map 2 Employment rate, (ages 20-64), 2013 - Distance to National 2020 target 
                                     
 Box on The European Employment Strategy and the EU-level labour market policy response to the crisis Since 1997, the European employment strategy has been aimed at creating more and better jobs by striking a balance between flexible job arrangements and secure transitions between jobs. It relies on the open method of coordination to guide employment policy in Member States. While objectives, priorities and targets are agreed at EU level, national governments are responsible for formulating and implementing specific policies with the European Commission providing advice, monitoring and help in coordination. This strategy is linked to the annual growth survey, which sets out the EU priorities for the coming year. It comprises: ·   the Employment guidelines - common priorities and targets for employment policies. ·   the Joint employment report which reviews the progress made ·   the National Reform Programmes ·   country-specific recommendations In 2012, the Commission adopted a set of proposals for action over the medium-term on three fronts - job creation, operation of the labour market and governance at the EU level. This Employment Package puts emphasis on skills development, including through lifelong learning, and on tackling skills mismatches. A number of initiatives were included as part of the overall package in 2012-2013: ·   The Youth Employment Package (2012) aims to reduce high youth unemployment and social exclusion, in part through a Youth Guarantee. In 2013, the Council called on Member States to ensure that all young people under 25 receive a good quality offer of employment, continued education, an apprenticeship or a traineeship within four months of leaving formal education or becoming unemployed. Member States eligible for the Youth Employment Initiative are expected to draw up Youth Guarantee Implementation Plans. ·   The European Alliance for Apprenticeships (2013) aims to improve the quality and supply of apprenticeships across the EU and change attitudes towards these. ·   A Quality Framework for Traineeships (2013) aims to enable young people to undertake good quality work experience to increase their employability. ·   The modernisation of the functioning of the pan-European job search facility (EURES) was promote, through a  proposal in 2014 for a regulation aimed at stimulating intra-EU labour mobility to reduce labour shortages in high growth areas and persistent high unemployment in other regions. ·   The Grand Coalition for Digital Jobs bringing together companies and organisations to cooperate in developing innovative training and teaching for jobs in ICT is aimed at facilitating the certification of skills and supporting worker mobility. In addition, in 2013 the Commission proposed to strengthen the coordination and surveillance of employment and social policies within the Eurozone to help to identify and tackle social and economic divergences. 

2.2.    Unemployment highest
in the EU in over a decade

The unemployment rate in the EU-28 fell from
9.3% in 2004 to 7.1% in 2008. Between 2008 and 2013, however, it rose to 10.9%,
higher than at any time for which data are available (since 2000). In the
EU-15, unemployment was 11.1% in 2013, higher than at any time since 1991 when
comparable figures first became available. 
The increase in unemployment has reversed the
trend towards diminishing regional labour market disparities. The rise in
unemployment has been especially marked in regions in Spain, Greece, Ireland and the Baltic States, in particular (Map 15), taking the rate to over 18% in
many cases (Map 14). 
Between 2008 and 2013, the unemployment rate
increased in 227 out of the 272 NUTS 2 regions. Virtually all of the regions where
it declined were in Germany. The Transition regions had the highest unemployment
rates in 2013, averaging 15% (Table 9). The increase in unemployment between
2008 and 2013 in these regions and in the more developed ones was much larger
than the decline between 2000 and 2008. As a result, in both groups,
unemployment in 2013 was higher than in 2000. The less developed regions
experienced a much bigger reduction in unemployment rates between 2000 and 2008
(of 5.8 percentage points) and while the impact of the crisis was also large
(increasing the rate by 4.9 percentage points), the rate was still lower than
in 2000.
Youth unemployment was 23% of the labour force aged
15-24 in 2013. One in four regions had a rate of more than 35%, the rate being
particularly high in southern Member States. In most regions, however, the
majority of the age group is not part of the labour force, in the sense of
being employed or actively seeking work. The NEET rate (the proportion of the
age group neither in employment nor in education and training) gives a more
accurate picture of the situation of young people as it covers all those aged
15-24 and not just those recorded as being part of the labour force. Between 2008
and 2013, the proportion of NEETs increased by 2 percentage points in the EU-28
to 13% of the age group. The rates were over 25% in some of the regions of Bulgaria, Romania, Italy, Spain and Greece, which also recorded the largest increases over the crisis
period (European Commission 2013[1]).
Table
2 Unemployment rate by
category of region, 2000-2013
   || More developed || Transition || Less developed || EU-28 
 Unemployment rate population aged, 2013 || 9.2 || 15.3 || 12.8 || 10.8 
 Change 2008 - 2013, in pp || 3.2 || 5.0 || 4.9 || 3.8 
 Change 2000 - 2008, in pp || -0.8 || -2.5 || -5.8 || -2.2 
Source: Eurostat and REGIO calculations
 Map 3 Unemployment rate, 2013 || Map 4 Change in unemployment rate, 2008-2013 
 Map 5 Youth unemployment rate, 2013 || Map 6 Population aged 15-24 not in employment, education or training, 2013 

2.3.      Women have far higher
unemployment rates in southern EU regions 

Unemployment of women relative to men differs
markedly across the EU. Overall, the rate for women was the same as for men in
2013 though it was 0.9 of a percentage point higher in 2008. The relative
decline is due to the concentration of job losses in the recession in
manufacturing and construction in which comparatively few women are employed.
Unemployment of women was at least 5 percentage points higher than for men in 15
regions in 2013, mostly located in Greece and Spain (Map 18). In contrast, it
was 3 percentage points lower in 16 regions, located mainly in Ireland, Bulgaria, the UK and Portugal. 
Because of differences in rates of
participation in the work force, women had a lower employment rate than men in
every region in the EU in 2013. The biggest differences were in Southern EU
regions, especially in Malta (where the rate for women was 32 percentage points
lower than for men), Greece, southern Italy and parts of Spain. On the other hand, in two regions in Finland (Åland and Etelä-Suomi) female
employment rates were close to those of men. 
The persistence of such large differences
between employment rates for men and women will make it difficult, if not
impossible, to reach the 2020 employment targets. The gap in employment rates is
heavily influenced by the type of employment opportunities open to women, the
wages offered and the availability and cost of childcare as well as elderly
care, since caring responsibilities are still predominantly borne by women. 
In terms of educational attainment, however,
women outperform men in most regions. For every 100 men aged 25-64 with a
tertiary qualification in 2013, there were 109 women. Over the past 20 years
the proportion of women with tertiary education has caught up with and
surpassed that of men. While, in 2013, there were only 98 women aged 50-54 with
tertiary education per 100 men –i.e. those who mostly completed their education
in the 1980s – there were 126 women aged 30-34 per 100 men (i.e. those who
completed their education 20 years later in the 2000s) (Map 19). 
This tendency is also evident at regional
level. For those aged 30-34, in nine out of ten regions, there were more women
than men with a university degree or equivalent in 2013. The main exceptions
are Western German regions, which have a tertiary education system that requires
more years of study to graduate than in most of the rest of the EU. With the
transition to the bachelor-masters system, this difference might well disappear
in the future. 
 Map 7 Difference between female and male unemployment rate, 2013 || Map 8 Difference between female and male employment rate, 20-64, 2013 
 Map 9 Gender balance of population 50-54 with tertiary education, 2011-13 || Map 10 Gender balance of population 30-34 with tertiary education, 2011-13 

2.4.    Reduction in early-school leavers
is on track

Reducing the number of early school leavers
(i.e. those who fail to complete upper secondary education) is critical not
only to raise the skills of the work-force but also for the employment
prospects and life chances of the people concerned. People with at least an upper
secondary qualification are much more likely to find a job, earn a higher
income and have a longer life expectancy than those with a lower level of education.

The Europe 2020 target is to reduce the share
of early school leavers among the population aged 18-24 in the EU to 10% as
against 11.9% in 2013, which was already significantly lower than in 2008
(14.8%).  While this reduction may in part be attributable to a more difficult
employment environment, there is also evidence of structural improvements and
the trend is expected to continue, even if at a slower pace.In 2013, 82 out 221
regions for which there are data and a national target (the UK has not set a target)
had reached the target. Around two-thirds of these regions were more developed
ones. 
Table
3 Early school leavers and
distance to national target, 2008-2013
   || More developed || Transition || Less developed || EU-28 
 Early school leavers (18-24 years), 2013 || 11.1 || 15.5 || 12.1 || 11.9 
 Reduction 2008 - 2013, in pp || 3.3 || 3.7 || 1.0 || 2.8 
 distance to target 2013-2020 || 0.5 || 4.0 || 3.3 || 1.9 
 Share of regions* that have reached national target in % || 47 || 22 || 25 || 37 
 * Includes only regions with data and a national target ||   ||   
 Source: Eurostat ||   ||   
 Map 11 Early leavers from education and training aged 18-24, average 2011-2013 || Map 12: Early school leavers aged 18-24 in 2011-13 - Distance to national 2020 target 
To boost growth
and jobs and to prevent skill bottlenecks and shortages, education and training
systems have to be able not only to absorb an increasing number of students but
to provide good quality teaching. Surveys carried out by the OECD in this regard
(Map 41) reveal that about 20% of the 15 year olds tested under PISA have an insufficient understanding of what they read and an even larger proportion
have insufficient competence in maths. In many EU countries, there are still a large
number of ‘low achievers’ in the two basic skills as well as in the third basic
skill, scientific literacy. 
In Bulgaria, Romania and Cyprus, the proportion of low achievers has consistently been over 30%, while
in Greece, there are over 30% of low achievers in maths but less in the other
two areas. By contrast, three Member States (Finland, Estonia and Netherlands) have already reached the EU 2020 benchmark of no more than 15% of low
achievers in reading, maths and scientific literacy and Germany, Denmark, Ireland and Latvia are very close. 
Map
13 Low achievers in
mathematics, reading and science
Source: OECD PISA

2.5. Lifelong
learning is stagnating

Continued learning after initial education and
training is necessary for people to maintain and develop their skills, to adapt
to structural change and technical developments, to retain their jobs, to
progress in their careers or to get back into employment. In view of its
importance, a benchmark objective has been established by the Council for 15%
of adults in the EU to be participating in lifelong learning by 2020[2].
[1]        European
Commission, 2013, Employment and Social Developments in Europe 2013, Directorate-General
for Employment, Social Affairs and Inclusion, Publications Office of the
European Union, 2014, ISBN 978-92-79-33878-6 (print), doi:10.2767/6072 (print)
[2]
       European
Commission, 2012, Education and training monitor 2012, Publications
Office of the European Union, 2012, ISBN 978-92-9201-350-9, doi: 10.2797/51172
In 2013, the figure was just 10.5%, only
slightly higher than in 2004 (9.1%). As a result, it may be difficult to
achieve this objective. Just over one in four regions (77 out of 266) exceeded the
15% target, with regions in the three Nordic Member States having the highest
figures (above 20%). In contrast, in regions in Bulgaria, Greece, Romania, Hungary, Slovakia and Poland, the proportion remained below 5% (map). The
importance of improving adult learning policies is also emphasised in the country-specific
recommendations issued by the Council under the European Semester – which, in
2013, included a recommendation on lifelong learning for Estonia, Spain, France, Hungary and Poland [1].
Map 1 Participation of adults aged 25-64 in education
and training, 2013
Education and training 2020 (ET2020)
Three
benchmarks for 2020 have been set in addition to the headline targets for
early-school leavers and participation in tertiary education:
–          At least 95% of
children between the ages of four and starting compulsory primary schooling
should participate in early childhood education; 
–          Less than 15% of
15-years olds should have insufficient abilities in reading, mathematics and
science 
–          At least 15 % of
adults (age group 25-64) should participate in lifelong learning 
–          Considerable progress
has been achieved through cooperation – particularly through support of
national reforms of lifelong learning, the modernisation of higher education
and the development of common EU means of ensuring good quality education,
transparency in qualifications and mobility between countries.
The budget for the EU programme on
education and training Erasmus+ has been increased by 40% to EUR 14.7 billion
in the 2014-2020 period, so providing opportunities for over 4 million
Europeans to study, train, gain work experience and volunteer in another
country.

2.6. Adult proficiency
in literacy and numeracy needs to be increased in several EU Member States
according to OECD PIAAC 

The ability to read and understand both
literary and numerical information is essential for full participation in
society and the economy. Without adequate skills of
these kinds, people are kept at the margins of society and face significant
barriers in entering the labour market. 
Unfortunately in most Member States, there are
substantial numbers of people who have low levels of proficiency in reading and
maths, as indicated by the Survey of Adult Skills (PIAAC) [2] carried out by the OECD which assesses the literacy, numeracy and
problem-solving ability of people aged 16 and over. According to the latest
version (2013), the highest levels of numerical and literacy skills are in Finland, the Netherlands, Sweden and Norway together with Japan. By contrast, levels are relatively
low in Spain and Italy, where many adults struggle with the most basic skills.
The survey shows, moreover, that high levels of inequality in literacy and
numeracy skills are related to inequality in the distribution of income.
 Figure 1 Adult literacy proficiency, 2012 || Figure 2 Adult numeracy proficiency, 2012 
 SOURCE: OECD (2013), OECD Skills Outlook 2013                

3.     Poverty and exclusion increase due to the crisis 

Ensuring inclusive growth is at the heart
of the Europe 2020 strategy. It means that social policies should seek to
empower people to find work, contribute to the modernisation of labour markets,
invest in skills and training, fight poverty and reform social protection
systems so as to help people anticipate and manage change and build a cohesive
society. The aim is to ensure that the benefits of economic growth spread to
all levels of society throughout the Union. 
Most notably, the Europe 2020 strategy
introduced a stronger focus on poverty and social exclusion. It also introduced
a new summary measure of this with three indicators: being severely materially
deprived, living in a household with zero or very low work intensity and being
at risk of poverty (see box). This section examines, first the three underlying
indicators and then the summary measure. 
These indicators are all derived from data
collected by the EU-SILC – EU Survey on Income and Living Conditions – the only
comparable source of such data for EU Member States, though it does not as yet
provide regional indicators in all Member States. (In 2014, however, the
European Commission is providing support to national statistical institutes to
produce more regional level data.) 

Box: What does
it mean to be ‘at-risk of poverty or social exclusion’ (AROPE)?

People are considered to be at risk of
poverty or social exclusion if they experience one or more of the following
three conditions:
·   Being severely materially deprived: with living conditions constrained by a
lack of resources as measured in terms of being deprived of four of nine items:
unable to afford 1) to pay rent/mortgage or utility bills on time, 2) to keep
their home adequately warm, 3) to face unexpected expenses, 4) to eat meat,
fish or a protein equivalent every second day, 5) a one week holiday away from
home, 6) a car, 7) a washing machine, 8) a colour TV or 9) a telephone
(including mobile phone).
     This indicator captures absolute
poverty in some degree and is measured in the same way in all Member States.
·   Living in a jobless household or household
with very low work intensity:
where on average those of working-age (18-59) worked less than 20% of their
potential total working hours over the past year, either because of not being
employed or working part-time rather than full-time (students are excluded from
the calculation).
·   Being at risk of poverty: living in a household with an
‘equivalised disposable income’(i.e. adjusted for the size and composition of
households) below the at-risk-of-poverty threshold, set at 60% of the national
median equivalised disposable income. This is a measure of relative poverty.
The total number of people at
risk of poverty or social exclusion is less than the sum of the numbers in each
category, as many fall into more than one of them.
Whereas, aggregate, national level
indicators often hide important differences between regions or areas, a
comprehensive analysis of poverty, its determinants and poverty-reducing
interventions will often require a focus on poverty information that is further
geographically disaggregated. In this section, these indicators are examined
primarily in relation to the degree of urbanisation, a classification which
distinguishes cities from towns and suburbs and from rural areas at the local
level. For ease of presentation, rural areas are combined with towns and
suburbs. This enables the main types of area in which poverty and exclusion are
concentrated to be identified. In Western Member States, these are mainly
cities, in Central and Eastern Member States, mainly rural areas.

3.1.    Severe
material deprivation is highest in the towns,
suburbs and rural areas of less developed Member States

Some 11% of the population was identified as
being severely materially deprived in the EU-27 in 2005. This fell to 8% in
2009 but due to the crisis increased back to 11% in 2012. There is a close link
between the measure and levels of income and economic development of countries.
It is highest in Bulgaria (44%), Romania (30%), Latvia and Hungary (both 26%). 
In Bulgaria, Romania and Hungary, deprivation rates are much lower in cities – 12 percentage points lower in Bulgaria and 8 percentage points lower in Romania and Hungary (Figure 25). In cities in Austria, Ireland, UK and Belgium, by contrast, deprivation rates are between 8% and 10%, on average
5 percentage points higher than in the rest of the country.
Between 2008 and 2012, deprivation rates
increased by 7-8 percentage points in Greece, Hungary, Lithuania, Latvia and Italy. In the two Baltic States and Greece, deprivation rates increased more
in cities (see figure), while in Italy and Hungary they increased more in areas
outside. 
In Austria, Romania and Poland, deprivation rates declined by between 2 and 4 percentage points. In Poland and Romania, rates in towns, suburbs and rural areas fell by over than 5 percentage points
(compared to 3 percentage points in cities in the first and zero in the
second).
Overall, severe material deprivation remains
highest in the less developed Member States, especially in rural areas, towns
and suburbs. In more developed Member States, deprivation tends to be low but
higher in cities than elsewhere. The crisis has led to substantial increases in
deprivation in a number of Member States, but it has not altered this basic
pattern.
Figure 3 Severe material deprivation by degree of
urbanisation, 2008-2012
Source: Eurostat

3.2.    Very low work intensity in more developed MS is concentrated in cities

Compared to deprivation, very low work
intensity  is more evenly distributed across the EU. In 2008[3], the proportion of
people living in low work intensity households varied from 14% in Ireland to 5% in Cyprus. The crisis led to increases of between 5 and 10 percentage points by 2012[4] in Lithuania, Latvia, Spain, Greece and Ireland. Over the same period, there was a small decline in Poland and Germany, where the crisis had much less of an effect on employment (in Germany, the employment rate increased). 
The rate of low work intensity is between 5 and
9 percentage points lower in cities than in other areas in Bulgaria, Ireland, Lithuania, Slovakia, Hungary and Croatia. In contrast, it is 5 percentage points
higher in cities in the UK, Denmark, Germany, Belgium and Austria. In general, therefore, low work intensity is more prevalent in cities in more
developed Member States, with the exception of Ireland. This juxtaposition of
joblessness in cities with the many employment opportunities they offer is
sometimes referred to as the urban paradox. 
The crisis seems to have had little effect on
this pattern. Increases in low work intensity were higher in cities than in
other areas in Greece, Sweden, Portugal and Austria. In Germany, the rate in cities did not change but in other areas it declined by 2 percentage
points. In the Czech Republic, the exact opposite occurred. 
Figure 4 Very low work intensity by degree of urbanisation,
2008-2012
Source Eurostat

3.3.    Higher urban risk of poverty in
more developed MS and a higher risk in towns, suburbs and rural areas in less
developed MS

The at-risk-of-poverty rate is a relative
measure of poverty. Two aspects are important to take into account: 
(a)        Because the poverty
threshold is set at the national level, someone with a given level of income
can be considered at risk of poverty in one country and not at risk in another
where income levels are generally higher. 
(b)       The at-risk-of-poverty
rates are sensitive to changes in overall income. Someone whose income remains
constant between two years can find themselves above the at-risk-of-poverty
threshold if median income declines or below the threshold if median income
increases. The reduction in household income which occurred in many countries
as a result of the economic recession reduced median income and therefore did
not lead to as big an increase in the proportion of people at risk of poverty
as might have been expected – indeed, in some country it led to a fall
For example, in Latvia, the at-risk-of-poverty
rate declined from 26% to 19% between 2008 and 2012[5], primarily because
overall income levels fell. If the poverty threshold had remained at the 2008
level, the at-risk-of-poverty rate would have risen from 26% to 36%[6].
Of the three indicators, this shows the biggest
differences between cities and the rest of the country. In 15 Member States, most
of them in the EU-13, at-risk-of-poverty rates were at least 4 percentage
points lower in cities than elsewhere (Figure 27), indicating that people tend
to earn more in cities than in other areas. 
In 6 EU-15 Member States, on the other hand, at-risk-of-poverty
rates were at least 4 percentage points higher in cities than elsewhere,
highlighting the more unequal distribution of income in cities than in other
areas. 
Figure 5 At-risk-of-poverty rate by degree of urbanisation,
2008-2012
Source Eurostat
Between 2008 and 2012, at-risk-of-poverty rates
increased in 17 Member States in part due to the crisis. Overall across the EU,
rates increased more in cities (by 1 percentage point on average) than in other
areas (0.3 of a percentage point). The difference was particularly wide in Greece, where the rate increased by 6 percentage points in cities and by 1 percentage point
in other areas. Poverty rates in cities in Germany increased by 4 percentage
points and in Austria by 6 percentage points. In the Netherlands, poverty rates
in cities increased by 2 percentage points while poverty rates in other areas
fell by 4 percentage points. As result, in 2012, at-risk-of-poverty poverty
rates in cities were higher than in other areas, while in 2008 they were lower.
Given the marked territorial dimension of
poverty rates, national level indicators hide important differences. Policies
addressing poverty could benefit from a more detailed geographical breakdown of
the prevailing situation and of the main determinants. This is why the European
Commission has launched an exercise together with ESPON and the World Bank to
produce more detailed poverty maps for each Member State. 
Map 2 At-risk-of-poverty rates, 2011
 Map 3 Population at-risk-of-poverty-or-social-exclusion, 2012 || Map 4 Population at-risk-of-poverty-or-social-exclusion in 2012, distance to national 2020 target 

3.4.    Cities in less developed Member
States are close to the 2020 targets, while cities in more developed Member
States lag behind

The Europe 2020
strategy aims to reduce the number of people at risk of poverty or social
exclusion by 20 million relative to 2010 or to around 19.5% of the total
population. Already in 2012, most of the regions in Austria, Czech Republic, the Netherlands and the Nordic Member States as well as one or more regions in Spain, Italy, Slovakia, Slovenia and Belgium had reached this target rate (Map 44). (For Germany and France, a regional breakdown is not yet available, though their national rates are in
both cases below the 2020 target[7].)
The difference from
the national target is typically widest in the less developed regions (Map 45).
For example, in Italy, Spain, Hungary and Bulgaria, the least developed regions
are all more than 14 percentage points away from their national targets,
suggesting perhaps that Cohesion Policy in these regions should include
significant measures for reducing the number of people at risk of poverty or
social exclusion.
Between 2008 and
2012[8], the number of people
in the EU at risk of poverty or social exclusion increased by 6.5 million to almost
a quarter (24.8%) of the population. Those most affected are people of working
age because of the significant increase in unemployment and the downward
pressure on earnings in a context of persistent job shortages. 
In 2012, the rate in
cities in 7 Member States was already, on average, below the respective
national 2020 targets (Figure 28). In three Member States, this was the case in
‘non-city’ areas (i.e. towns and suburbs and rural areas). (Note that the UK, Sweden and Croatia have not set national targets.) To formulate policies for reducing rates, it
is important to know what type of area those at risk of poverty or exclusion
are concentrated in, since, to some extent at least, the measures need to
differ because of differences in the underlying factors.
Figure 6 At risk
of poverty or exclusion by degree of urbanisation, 
2008-2012 and national 2020 targets
 Box on Social inclusion and social protection policies The fact that at-risk-of-poverty and social exclusion target is included in the Europe 2020 strategy is a reflection of the stronger focus  on social issues in the Europe 2020 policy framework. National Governments have primary responsibility for implementing social policy reforms with regional and local authorities also playing an important role, especially in providing services. Some Member States had already taken steps to re-structure their social protection systems before the crisis and these have tended to weather the crisis better in both economic and social terms. The European Platform against poverty and social exclusion was set up to help Member States s reach their poverty and social exclusion target, including through more effective use of EU funds. A Social Investment Package was adopted by the Commission in 2012. It has three strands, the first relating to tackling childhood disadvantage at an early stage by providing accessible and good quality education and measures to improve the economic situation of the families concerned. The second involves investing in skills, even in a climate of fiscal consolidation, by supporting training and affordable care services as well as job search assistance. The third entails simplifying the administration of benefits and making it easier to obtain support. The European Globalisation Adjustment Fund, established in 2006, provides support to workers made redundant as a result of changes in patterns of world trade or, more recently, because of the crisis. In the 2014-20 period, it will also provide support for youth employment at regional level. The PROGRESS programme (EU Programme for Employment and Social Solidarity) is an EU-wide platform for exchange and learning, aimed at producing evidence on the effectiveness of European employment and social policies as well as encouraging wider involvement, including of social partners and civil society organisations, in policy-making. PROGRESS Micro-Finance Facility (set up in 2010 in response to the crisis) is intended to increase the availability of microfinance for people who are socially and economically disadvantaged, very small firms and social economy organisations. In 2014-2020 period, the two parts of PROGRESS and the European Employment Services (EURES) network, form part of the new programme for Employment and Social Innovation (EaSI). This is intended to support Member States in their efforts to design and implement employment and social reforms at all levels through helping to coordinate policy and to identify, and exchange information on, examples of best practice. The new Fund for European Aid to the most deprived (FEAD) is intended to further social cohesion through non-financial (in-kind) assistance to those experiencing the most deprivation. 

3.5.    Quality of life in European
cities varies

Surveys of people’s perception of the quality
of life in European cities which are carried out on a regular basis are
intended to give a snapshot of opinions on a range of urban issues. The latest
one for 2013[9]
measures the satisfaction of those living in 79 cities in the EU. The responses
to 7 indicators are examined below for 16 selected cities to illustrate the
situation across the EU[10].
Interviewees were asked to judge their
satisfaction with the following features of the cities in which they lived:
public transport, air quality, safety, quality of city government, job
opportunities, the cost and availability of housing and the integration of
foreigners. The results are plotted in spider graphs and compared with the
median level of satisfaction in the EU.
They reveal wide differences between cities on
how the people there view the quality of life as well as indicating the
strengths of some cities and the difficulties encountered in others. Some adverse
opinions reflect the impact of the crisis on people's well-being as well as on
city finances. This is more evident in cities in countries hit hard by the
recession. In Athens, Oviedo and Palermo, the lack of employment opportunities
is seen as the major problem. In the big cities in northern Europe - Helsinki, Munich, Hamburg, Paris and London – on the other hand, the majority consider it relatively
easy to find a job. At the same time, because jobs are concentrated in these
cities which attracts people to live there, this puts pressure on housing,
increases the cost and reduces levels of satisfaction. 
Satisfaction with levels of safety, air quality
and public transport tends to be related to the perceived efficiency of the
city authorities. Cities where there is a relatively high opinion of the
latter, such as Aalborg, Munich, Hamburg and Rostock, also show high
satisfaction levels with the former, while the reverse is the case in Oviedo, Athens, Palermo, Paris, Madrid and Sofia where dissatisfaction was expressed with
both.

3.6.    Crime rates are higher in urban
regions, border regions and tourism destinations

Criminal activity is not evenly distributed
across the EU. Highly urbanised areas, tourist destinations and some border
regions have considerably higher numbers of registered crimes per head than
others, though these figures need to be interpreted with a great deal of
caution. Many crimes, such as burglaries, are under-reported, while victims may
live in a different region from the one where the crime was committed, such as
if they were robbed when on a visit or had their car stolen, which can lead to
an over-estimate of crime rates in some regions and an under-estimate in
others.
Robberies are more frequent in regions with
large cities, as, for example, in Belgium in the Brussels region or the regions
in which Antwerp, Liege and Charleroi are situated. Burglaries also occur more
often in the more urban NUTS 3 regions, such as those where Vienna or Sofia are located, than elsewhere. This is equally the case for regions with many
tourists, such as those along the Mediterranean coast of France and Spain or the Algarve in Portugal. The same applies to thefts of motor vehicles, which
show high rates a well in some border regions, such as those along the border
between Belgium and France or between Germany, Poland and the Czech Republic. 
Crime can have a major impact on economic and
social development, instilling fear into people and deterring entrepreneurs
from starting businesses. It gives rise to additional costs which can affect
the poorer members of society in particular and discourage potential investors.
Development strategies in regions with high crime rates cannot ignore these
aspects.
 Map 5 Registered thefts of motor vehicles per capita, 2008-2010 || Map 6 Registered domestic burglaries per capita, 2010 

4.     movement
of people within and between Member States is spurred by disparities in
employment, wages and health
4.1.    The EU is highly urbanised and is
still urbanising but only slowly

The change in population in the EU over the
long-term gives a broader perspective to more recent tendencies, indicating
whether they are part of a long-term trend or represent a break with the past.
It also provides a point of comparison, in the sense of showing whether changes
are unprecedented in scale or relatively minor as compared with those which
have occurred over the previous 50 years. In addition, investment in
large-scale infrastructure needs to be planned in the light of the likely
population change over coming decades and past trends can help to project this.
Rapid population growth gives rise to adjustment costs as a result of the
increased need for services and infrastructure – schools, hospitals and so on –
which may be difficult to finance if public funds are in short supply. Slower
growth on the other hand, enables investment to be planned more easily, when,
for example, a school or hospital needs renovating or replacing. 
Regions losing population rapidly may need to
downscale their services and infrastructure. One in 20 NUTS-3 regions lost more
than 10% of their population between 2001 and 2011, leading in all probability
to an oversupply of housing, public services and so on. Several cities in Eastern Germany lost so many people that neighbourhoods were demolished to reduce the city
to a more viable size. 
Over the 50 years, 1961-2011, population growth
in the EU was at its highest in the 1960s when the increase was 8% over the
decade. Growth slowed gradually up to the 1990s to an increase of around 2% in
the decade but picked up to an increase of some 3.5% between 2001 and 2011.
These changes are reflected in the relative number of NUTS-3 regions with
population growth of more than 10% a decade. Between 1961 and 971, one in three
grew by more than 10%, in the next decade, and in the 1980s, 1990s and 2000s
less than one in 10. 
The regions with a population reduction of more
than 10% a decade followed a different pattern than might be expected. In the
1960s, this occurred in 5% of regions, located primarily in Portugal, Greece and   Spain. In the 1970s, the proportion fell to around 2.5% and in the 1980s and
1990s to 1.5%. In 1989, the Berlin Wall came down and there were regime changes
throughout Central and Eastern Europe around the same time, leading to a
substantial increase in migration. In the 1990s, just over 4% of regions lost
more than 10% of their population and in the 2000s, 7%, the regions concerned
being located mainly in the Baltic States, Romania, Bulgaria, Croatia and Eastern Germany.
Growth in the 1960s was mostly concentrated in
the urban regions, where there was an increase over the decade of 12%, as
against 9% in intermediate regions and 1% in rural regions. 
After 1971, differences between growth in the
EU-15 and the EU-13 became more marked. Between 1971 and 2011, population in
the EU-15 grew by about 4% a decade. Growth in urban and intermediate regions
was slightly above average while in rural regions, it was around half the
average. 
In the EU-13, population growth slowed down
after 1981 and became negative after 1991. In all three types of region,
population fell during the 1990s and continued to fall in rural regions in the
2000s (by 3%), while it increased in the 2000s in urban regions (by just under
1%) (Table 11).
Table
1 Population change by
urban-rural typology, 1961-2011
 Population change in in % || URBAN RURAL TYPOLOGY || 1961-1971 || 1971-1981 || 1981-1991 || 1991-2001 || 2001-2011 
   ||   ||   ||   ||   ||   ||   
 EU15 || Urban || 11.6 || 4.4 || 2.9 || 3.6 || 6.4 
 EU15 || Intermediate || 7.8 || 4.9 || 3.6 || 3.9 || 4.5 
 EU15 || Rural || -0.3 || 1.8 || 1.5 || 2.4 || 2.4 
   || Total || 7.8 || 4.1 || 2.9 || 3.5 || 5.0 
   ||   ||   ||   ||   ||   ||   
 EU13 || Urban || 14.9 || 11.0 || 4.5 || -2.4 || 0.7 
 EU13 || Intermediate || 11.2 || 9.6 || 3.5 || -0.6 || -0.3 
 EU13 || Rural || 3.6 || 4.2 || 2.0 || -2.8 || -3.2 
   || Total || 8.5 || 7.6 || 3.1 || -1.9 || -1.3 
   ||   ||   ||   ||   ||   ||   
 EU28 || Urban || 12.0 || 5.1 || 3.1 || 2.9 || 5.7 
 EU28 || Intermediate || 8.6 || 6.1 || 3.6 || 2.8 || 3.4 
 EU28 || Rural || 1.2 || 2.7 || 1.7 || 0.3 || 0.3 
   || Total || 8.0 || 4.9 || 2.9 || 2.2 || 3.6 
Source: Time series of LAU2 population
data, NSI, DG REGIO / Spatial Foresight
[1]       http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm
provides access to all CSRs.
[2]       OECD (2013), OECD Skills Outlook 2013: First Results from
the Survey of Adult Skills, OECD Publishing http://dx.doi.org/10.1787/9789264204256-en

[3]       Note that these years relate to the time of the survey. The
year over which work intensity is measured is the preceding calendar year,
except in the UK (the previous tax year) and Ireland (the preceding 12 months).
[4]       For most countries, the figures for 2012 relate to the 2011
calendar year; see previous footnote..
[5]       This means between the 2007 and 2011 income years.
[6]       This is termed the at-risk-of-poverty rate anchored at a
point in time.
[7]       For Germany, it should be noted, the national indicator used,
differently from other Member States, is long-tern unemployment.
[8]       Between the 2007 and 2011 income years.
[9]       European
Commission, 2013, Quality of life in cities, Perception survey in 79 European
cities Flash Eurobarometer 366 
[10]     Responses like "do not know" have been eliminated
during the elaboration of the data.
Map 1
Population change, 1961-2001
These changes in population growth were
accompanied by changes in the degree of urbanisation in the EU. Compared to the
rest of the world, the EU, especially the EU-15, was already highly urbanised
in 1961. In the 50 years since, the proportion of the population in the EU-15
living in cities (42%) has not changed (Table 12). Between 1961 and 1991, the
population living in towns and suburbs increased from 28% to 32% and the
proportion in rural areas fell from 30% to 25%. Since 1991, the proportions
have remained broadly unchanged. Accordingly, 70% of the population in the
EU-15 lived in urban areas (cities, towns and suburbs) in 1961, this rising to
75% in 1991 and remaining at this level up to 2011.
In the EU-13, the degree of urbanisation is
less. In 2011, 60% of the population lived in urban areas, though this was
significantly more than 50 years earlier (45%). As in the EU-15, almost all the
increase occurred between 1961 and 1991, though in contrast to the EU-15, the
increase occurred in both cities (from 25% to 34%) and towns and suburbs (from
20% to 25%). Between 1991 and 2011, the proportions changed relatively little,
with only a small increase in towns and suburbs.
Table
1 Population by degree of
urbanisation, 1961-2011
   ||   || 1961 || 1971 || 1981 || 1991 || 2001 || 2011 
 EU-15 || Cities || 42.4 || 43.6 || 43.4 || 42.9 || 42.2 || 42.3 
   || Towns and suburbs || 27.8 || 29.5 || 31.0 || 31.8 || 32.5 || 32.6 
   || Rural areas || 29.8 || 26.9 || 25.6 || 25.3 || 25.3 || 25.0 
   || Total || 100.0 || 100.0 || 100.0 || 100.0 || 100.0 || 100.0 
   ||   ||   ||   ||   ||   ||   ||   
 EU-13 || Cities || 25.4 || 29.0 || 32.6 || 34.2 || 33.9 || 33.8 
   || Towns and suburbs || 19.7 || 21.4 || 23.1 || 24.5 || 25.1 || 25.7 
   || Rural areas || 55.0 || 49.6 || 44.3 || 41.4 || 41.0 || 40.4 
   || Total || 100.0 || 100.0 || 100.0 || 100.0 || 100.0 || 100.0 
   ||   ||   ||   ||   ||   ||   ||   
 EU-28 || Cities || 38.6 || 40.3 || 40.9 || 40.9 || 40.4 || 40.5 
   || Towns and suburbs || 26.0 || 27.7 || 29.2 || 30.1 || 30.8 || 31.2 
   || Rural areas || 35.5 || 32.0 || 29.9 || 29.0 || 28.8 || 28.3 
   || Total || 100.0 || 100.0 || 100.0 || 100.0 || 100.0 || 100.0 
 Note Only partial data for Portugal and Slovenia ||   ||   ||   ||   
 Source: Time series of LAU2 population data, NSI, DG REGIO / Spatial Foresight ||   ||   

4.2.    Net migration is the main source
of population growth in the 2000s

Total population growth between 2001 and 2011
was modest at 3.8% in the EU-28. The contribution of natural growth (births
less deaths) was small (only 0.4%), most of the increase coming
from net inward migration from outside the EU. 
Whereas migration (inside as well as from
outside the EU) increased population in all types of region in the EU-15, it
did so in urban regions in the EU-13 and since the natural change was negative
in all three types of region, growth occurred only in urban regions (Table 13).

In the EU-15, the natural change in population
was negative in rural regions but positive in intermediate and, most
especially, urban ones, which is the main reason why population in urban
regions grew twice as fast as in rural regions. 
Table
2 Population change,
natural change and net migration
by urban-rural typology, 2001-2011
 Population change, natural change and net migration by urban-rural typology, 2001-2011 
   || Predominantly urban || Intermediate || Predominantly rural || Total 
 Total change in % ||   ||   ||   ||   
   ||   || EU-13 ||   
 Total population change || 0.6 || -1.1 || -3.9 || -1.9 
 Natural population change || -1.2 || -0.7 || -1.8 || -1.3 
 Net migration || 1.8 || -0.4 || -2.2 || -0.6 
   ||   ||   ||   ||   
   ||   || EU-15 ||   
 Total population change || 6.8 || 4.7 || 3.1 || 5.4 
 Natural population change || 2.6 || 0.5 || -0.6 || 1.3 
 Net migration || 4.1 || 4.2 || 3.7 || 4.1 
   ||   ||   ||   ||   
   ||   || EU-28 ||   
 Total population change || 6.1 || 3.3 || 0.4 || 3.8 
 Natural population change || 2.2 || 0.2 || -1.0 || 0.7 
 Net migration || 3.8 || 3.1 || 1.5 || 3.0 
 Source: Eurostat ||   ||   ||   ||   
Children (those under
15) make up a smaller share of population in the EU-13 than the EU-15 and are
more concentrated in rural regions in the former and urban regions in the
latter (Table 14). The proportion of older people (those of 65 an over) is
significantly higher in the EU-15 than the EU-13. In the EU-15, they are
considerably more concentrated in rural regions than in the EU-13 where they
are spread evenly between the three types of region. 
Table
3 Population age structure
by urban-rural typology, 2012
   || Predominantly Urban || Intermediate || Predominantly Rural || Total 
 % of total population ||   ||   ||   ||   
   || EU-13 ||   
 population aged 14 or less || 14.0 || 15.0 || 15.2 || 14.9 
 population aged 65 or more || 15.6 || 14.8 || 15.7 || 15.3 
   || EU-15 ||   
 population aged 14 or less || 16.2 || 15.4 || 15.4 || 15.8 
 population aged 65 or more || 17.2 || 19.3 || 20.4 || 18.5 
   || EU-28 ||   
 population aged 14 or less || 16.0 || 15.3 || 15.3 || 15.6 
 population aged 65 or more || 17.0 || 18.2 || 18.6 || 17.8 
 Source: EUROSTAT, DG REGIO ||   ||   ||   ||   
 MT data are 2010 and DE8, ES63 and ES7 regions are 2011 ||   ||   
Map 2 Total population
change, 2001-2011
 Map 3 Natural population growth, 2001-2011 || Map 4 Net migration, 2001-2011 
Population in
the EU-13 border regions shrank over the last decade
Between 2001 and 2011, population in the ‘terrestrial’
border regions[1]
in the EU-13 shrank by more than the other EU-13 regions (by 3% as against 1% -
Table 15). This was primarily due to net outward migration which reduced the
population by 1.5% over the period, while in the rest of the EU-13 outward
migration was matched by inward. There was a natural reduction in population in
both areas, but more so in the terrestrial border regions. 
In the EU-15, by contrast, population increased
significantly between 2001 and 2011 (by 5%) as a result of both natural growth
and, more especially, net inward migration. Growth of population in the
terrestrial border regions (at 4%) was only slightly less than in the rest of
the EU-15 due to both a natural increase and net inward migration. 
On average, terrestrial border regions in
the EU-13, therefore, seem less attractive places to move to and/or to start a
family in than other parts of the EU-13 or EU-15. 
Table 4 - Population change, natural change and
net migration in terrestrial border regions, 2001-2011
   ||  Terrestrial Border regions || Other || Total 
   ||   ||   ||   
 Change over 10 years in % ||   ||   ||   
   ||   || EU-13 ||   
 Total population change || -3.10 || -0.99 || -1.89 
 Natural population change || -1.66 || -1.00 || -1.26 
 Net migration || -1.46 || 0.01 || -0.64 
   ||   ||   ||   
   ||   || EU-15 ||   
 Total population change || 4.05 || 5.56 || 5.41 
 Natural population change || 0.74 || 1.49 || 1.30 
 Net migration || 3.29 || 4.01 || 4.06 
   ||   ||   ||   
   ||   || EU-28 ||   
 Total population change || 0.91 || 4.54 || 3.78 
 Natural population change || -0.30 || 1.11 || 0.74 
 Net migration || 1.22 || 3.40 || 3.02 
Source: Eurostat,
DG REGIO
[1]
      ’Terrestrial’ border regions, are NUTS-3 regions which are eligible for
Cross-border Co-operation programmes under the ERDF Regulation, excluding those
which have only a martime border (see http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Regional_typologies_overview

Map 1 Regions[1] for cross-border cooperation, 2014-2020

4.3.    More foreign-born workers have
joined the labour market with varying success

As noted above, migration is the main source of
population growth in the EU, with the proportion of population born outside the
EU increasing from 2.9% to 4.1% between 2001 and 2012 (Figure 31). The increase
was particularly large in Spain (5 percentage points) and Italy (3.4 percentage points), in both cases many of the migrants coming from North Africa and Latin America. 
Figure 1 Population born outside the EU-27, 2001-2012
Although mobility within the EU does not, of
course, increase population in the EU as a whole, it increases it in some
Member States. The proportion of people born in a different EU country than
where they live increased between 2001 and 2012 from 1.4% to 2.7% (see Figure
32). This is similar to the increase in migrants from outside the EU, though it
still leaves the total proportion of EU-residents born in a different Member State smaller (2.7% as against 4.1%)
Figure 2 Population born in a different EU-27 country per
MS, 2001-2012
The impact of mobility between EU Member States
is, however, very uneven. The share of residents born in another Member state
remained stable or increased in all Member States between 2001 and 2012. In 6
Member States, however, the share remains very low with less than 0.3% of
residents born in another EU Member State. In Italy and Spain, the proportion
increased dramatically over the period from just 0.2% to 2.2% in the first and
from 1% to 4.5% in the second, most of the increase being accounted for by
people moving from Romania. In Ireland, UK, Cyprus and Denmark, the proportion doubled, in the first two, in particular, most of the increase coming from
movements from Poland, the Baltic States and the other 10 countries which
entered the EU in 2004.
Figure 3 Employment rate by country of birth, 2013
 
Source Eurostat, Germany is by citizenship (2012)

In 2013, the employment rate of people aged
15-64 born in the country in which they live (64.5%) was slightly lower than
that of those born in a different EU Member State (66.4%), but much higher than
for those born outside the EU (56%). In every EU-15 Member State, the
employment rate of those born outside the EU was lower than for those from
elsewhere in the EU. 
In half the Member States, the employment rate
of people born in another part of the EU is higher than that of the people born
in the country. In the UK, Portugal, Luxembourg and Finland, it was 5 or more percentage
points higher in 2013 (Figure 33). The differences in employment rates are in
part due to differences in age composition and in some cases education level.
They do, however, suggest that some of the concern about the impact of EU
mobility on social expenditure is misplaced (i.e. people tend to move to
another country in order to work rather than to take advantage of social
transfers).
The difference in the employment rate between
people born outside the EU – i.e. migrants – and those born in the country is
much bigger. In most Member States, the rate for those born outside the EU was
significantly lower than for the latter in 2013, especially in Belgium, Germany, the Netherlands and Sweden, where the difference amounted to around 18 percentage
points. The reasons for this are not easy to identify, but they are likely to
include lack of recognition of foreign qualifications (rather than low
education levels as such) and insufficient knowledge of the local language,
though also in some cases discrimination. Education and training can help to
reduce the gap along with employment growth. Public services could also lead by
example by ensuring that they include a proportionate number of migrants among
their staff.

4.4.    Life expectancy is high, but
regional disparities persist 

Life expectancy in the EU, which is a
reflection of well-being, is among the highest in the world. Of the 50
countries in the world with the highest life expectancy in 2012, 21 were EU
Member States, 18 of which had a higher life expectancy than the US. In the US, Hawaii and Minnesota are the only States with a life expectancy above the EU
average. In many of the southern US States, it is similar to that in Poland or Hungary (Maps 5 and 6). 
Differences between regions in the EU are
marked. Life expectancy at birth is less than 74 in many parts of Bulgaria as well as in Latvia and Lithuania, while overall across the EU it is over 80 years in two
out of every three regions. In 17 regions in Spain, France and Italy, it is 83 years or more. 
Differences in infant mortality (Map 7) and
road fatalities (see Map 8) are two major reasons for regional disparities in
life expectancy at birth. In 2012, in Sud-Est in Romania and Yugoiztochen and
Severozapaden in Bulgaria and Guadeloupe, infant mortality was over 10 deaths
per 1000 live births, while in 13 regions elsewhere in the EU, it was less than
2. The EU average in 2012 was 4.
In 39 regions, the number of road fatalities
per head was less than 30 per million inhabitants in 2012 compared to an EU
average of 56. These regions were primarily located in the UK, the Netherlands and Sweden and included 11 capital city regions and several other highly urbanised
regions. In part, the large number of capital city regions in the list is
because vehicles cannot drive quickly there and at low speeds they are far less
likely to cause a fatal accident. 
In 23 regions, the number of road fatalities
per head was over double the EU average: 138 or more per million inhabitants in
2012. These regions were mainly in Belgium, Bulgaria, Greece, Portugal and
Romania, The European Road Safety Action Programme, 2011-2020 has a target of
halving road deaths in the EU over this period, which means a reduction to
around 30 fatalities per million (the rate is below this at present in only 39
of the 272 NUTS-2 regions as noted above). The programme calls for safer roads,
education and training for road users, better enforcement, vehicle safety
measures, smart technology and better protection of road users at particular
risk.
High life expectancy combined with a low
fertility rate is the reason why the proportion of population aged 65 and over
is growing in the EU. In 2012, the proportion was 18% as against 16% in 2000.
In many regions the proportion was much larger. In almost a third of regions,
primarily located in Germany, Italy and Greece, it was 20% or more. In Liguria in Italy and Chemnitz in Germany, it was over 25%. Between 2000 and 2012, the
proportion increased in 9 out of every 10 regions, the largest rise occurring
in Brandenburg close to Berlin (from 15% to 22%). 
 Map 2 EU Life expectancy, 2011 || Map 3: USA Life expectancy, 2010 || 
 Map 4 Infant mortality, 2012 || Map 5 Road fatalities, 2012 
EU Health Strategy 
Considerable disparities between regions in
health exist across the EU. The health of people in less developed regions
tends to be significantly worse than in others, though there are also pockets
of poor health in more developed regions. A Treaty objective is to reduce such
disparities. 
Over the past decade, infant mortality has
declined in many of the less developed regions, leading to a reduction in
regional inequalities in this respect across the EU (the Gini coefficient
falling by 13% between 2000 and 2010), though inequalities remain wide. 
The Commission Communication (EC 2009[2]) on health inequalities
highlighted the fact that people with lower education, a lower level occupation
or lower income tend to die younger and are more likely to have health problems[3].
A number of barriers still exist to
accessing health services, specifically, the cost, distance, waiting time, a lack
of cultural sensitivities and discrimination. Distance is a particular issue in
some sparsely-populated, mountainous or remote regions as well as on islands.
The need for patients to pay for health services at the time of provision can
also limit access, especially for people who are socially or economically
disadvantaged. 
The EU Health Strategy proposes ‘smart’
investment in health through:
·   spending more effectively, but not
necessarily in larger amounts, on sustainable health services
·    promoting a healthy life-style
·   extending the coverage of health services
as a way of reducing inequalities and social exclusion .
In addition, as a result of the
cross-border health-care Directive, it has become easier to obtain healthcare
throughout the EU, especially in border regions. 

4.5.    Human development is improving in Central and Eastern Member States, but the crisis reduced it in Spain, Greece and Ireland

Given  such a wide variety of indicators, it is
difficult to fully assess the social issues in a region. To distil a simple,
yet comprehensive picture a composite indicator, such as the EU Human
Development Index (EU HDI)[4], can help to show the situation in regions at present and how it
has changed since 2008. 
 Map 6 EU Human development index, 2012 || Map 7 Change in the EU Human Development Index, 2008-2012 
The index is based on six indicators which
capture health, education and income/employment. The two health indicators are
life expectancy adjusted for health satisfaction and infant mortality. The two
education indicators are the share of people aged 18-24 not in employment,
education or training (NEETs) and the share of population aged 25-64 with a
tertiary education degree. The two income/activity indicators are gross
adjusted disposable household income per head in PPS terms (‘adjusted’ in the
sense of including social transfers in kind such as government-provided
education and healthcare services or childcare) and the employment rate of
population aged 20-64. 
In 2012, human development was considerably
lower than average in most central and eastern regions, Southern Italy and Greece. A number of central and eastern regions, however, score well, with the index in. Estonia and the capital city regions of Poland, Czech Republic, Slovakia, Hungary, Romania and Bulgaria being close to or above the EU average. 
In Austria, Germany, the Netherlands and the Nordic Member States., the index was high, indicating a good balance
between health, education and income. In the UK, France and Belgium, the situation varies, with some regions scoring highly and others below average, while in Spain and Italy, the divide is more marked, especially between the north and south in the latter. 
The changes between 2008 and 2012 are striking,
with a pronounced deterioration in the index in Greece, Ireland, Spain and Croatia and parts of Italy and to a lesser extent in some regions in the Netherlands, the UK and Denmark. 
In contrast, the index increased considerably in
all German and Polish regions, which were less affected by the crisis. At the
same time, many regions in countries which were affected by the crisis
nevertheless showed an increase in the index, including in the three Baltic
States, Finland, Sweden, Slovakia, Hungary and Czech Republic as well most regions
in Romania and Bulgaria. 
The EU HDI provides an alternative view of
development showing the progress made in the capital regions in the Central and
Eastern Member States and highlighting the continuing problems in Greece and Southern Italy. As an indicator, it comes closer than GDP to the issues that concern
people: health, education, income and employment opportunities.

5.     Conclusion

Between 2000 and 2008, many regions and
cities in the EU were able to achieve growth which was inclusive. Employment
rates increased, while poverty and exclusion were reduced.
The crisis has, however, led to a
significant deterioration in the situation since 2008, eliminating many of the
gains in increasing employment and reducing unemployment achieved over the
previous 8 years. While there are the first signs of recovery, it will take
time for these to give rise to significantly higher employment rates and to reduce
poverty and social exclusion.
On some fronts, however, progress is
continuing despite the crisis. For example, the number of early school leavers
has continued to fall and the Europe 2020 target may be reached even perhaps
before 2020. The gender gap in unemployment has been closed, though largely
because of a big increase in unemployment among men rather than any major fall
in the rate for women, which remains high in many southern regions. 
Poverty and social exclusion vary between
types of region in different ways across the EU and the crisis has not changed
this. Cities in less developed Member States tend to have lower poverty and
exclusion rates than other area, while the reverse is the case in cities in
more developed Member States. In some countries, the concentration of poverty
in cities is linked to the presence of a large number of migrants from outside
the EU who are poorly integrated into the labour market. 
The wide disparities in job availability,
wages and standards of living will continue to encourage people to move in
search of better opportunities and a higher quality of life, which emphasises
the importance of ensuring that they have the same access to employment as
those already living in the areas concerned. 
Cohesion Policy can play an important role
in helping to achieve the Europe 2020 targets considered here, by, in
particular, co-financing education and training and providing support for
measures to overcome obstacles to growth, so increasing the rate of job
creation as well as wages and income levels in lagging regions. At the same
time, it can help to ensure that women have the same opportunities for
employment and advancement as men, through for example, co-financing the
expansion of childcare facilities. It can also help to ensure that men and
women wherever they live have access to a high standard of healthcare through
supporting investment in hospitals and other medical facilities.
[1] Includes terrestrial and maritime border regions.
[2]       COM/2009/0567
[3]
Mackenbach J,
2006, Health inequalities: Europe in profile, report commissioned by the
UK Presidency of the EU, Erasmus Medical Centre, Rotterdam
[4]       Developed by the Joint Research Centre and the DG for
Regional and Urban Policy. See Hardeman
and Dijkstra L., 2014, Human Development Index, JRC Report (forthcoming
Chapter 3: Sustainable growth

1.     Introduction

Cohesion Policy has invested a large share
of its funds to encourage a shift towards a more sustainable mode of
development in EU regions. It has co-financed the installation of main water
supply to improve drinking water quality and urban waste water treatment
plants, invested in solid waste management and recycling schemes and
contributed to increased energy efficiency by for instance supporting the
modernisation of heating systems in private and public buildings or resource
efficient urban transport. It has also contributed to protecting the
environment by helping to set up a network of protected natural areas as part
of Natura 2000. 
Nevertheless, substantial challenges remain
to reduce the environmental impact of economic activity and improve the quality
of ecosystems. 
With the growing awareness of the
consequences of climate change, the EU has committed itself to limiting
greenhouse gas emissions and reducing consumption of fossil fuels. To this end,
an increasing share of Cohesion policy funding is being allocated to help bring
about a shift to a low-carbon economy, by, in particular, providing more
support for the production of renewable energy and improving energy efficiency.
Since climate change is likely to increase the risks of natural hazards such as
fires, droughts and floods, leading to more frequent disasters, funding has
also been allocated to mitigating these risks, and efforts will continue to be
made to ensure that this is used in the most resource-efficient way. 
Cohesion Policy also has indirect effects
on the environment and sustainability, since helping regions to develop and
improve their transport infrastructure may lead to higher energy use. It is
becoming increasingly important to mainstream environmental considerations
under the Cohesion Policy. Investment in energy efficiency can help to offset
this along with judicious choice of the infrastructure that is supported. Similarly,
a growing economy can lead to changes in land use. With the right national,
regional and local policies, changes can be limited and concentrated in areas
with good access to public transport, such as by redeveloping brownfields or by
encouraging new developments to locate close to existing public transport routes.
Preserving nature and natural resources,
saving energy, expanding renewable energy and green technologies, mitigating
and adapting to the effects of climate change and investing in disaster risk
management are not only necessary to address environmental challenges but they
can also provide new jobs and growth opportunitiesThe conservation and
enhancement of natural assets is also necessary to safeguard ‘ecosystem
services’ on which many economic activities implicitly rely, i.e. the services
provided by nature itself such as for instance clean air and waters or natural
ways of protecting against disasters and their consequences. Safeguarding the
continued provision of these ‘services’ results in cost-savings to the economy as
they contribute avoiding the costs for cleaning up contaminated land or
polluted rivers and preventing or mitigating costly (sometime man-made) natural
disasters such as floods or landslides.
EU Member States and regions vary markedly
as regards their pursuit of sustainable development. In some case, this is
because of differences in the geographical context or in the endowment of
natural assets, in others it reflects differences in environmental pressures
and natural resource management. Significant improvements could, therefore be
made by identifying what kind of action is required in what type of region.
This chapter covers four major issues –
first, climate change and the progress towards the Europe 2020 targets,
secondly, energy efficiency, air quality and transport, thirdly, resource
efficiency, especially of land use and, fourthly, potential ways of reducing
environmental impact and maintaining or improving ecosystems and the services
they provide. It ends by showing how other EU policies linked to sustainable
growth are affecting cohesion.

2.     The
EU needs to mitigate and adapt to Climate change

A world-wide process of climate change is
currently underway as a consequence of increases in greenhouse gasses in the
atmosphere from human activities. Since the late 19th century, the
Earth's atmosphere and oceans have steadily become warmer and this is projected
to continue and even to quicken in the coming years. Since the early 20th
century, the Earth’s mean surface temperature has increased by almost 1°C, with
two-thirds of the increase occurring since 1980.
Climate change affects our economies,
societies and ecosystems in many different ways. It has a strong territorial
dimension. Its effects vary significantly across regions, which differ in both
their exposure to climate change and their ability to cope with it, reflecting
their different physical, environmental, social, cultural and economic
characteristics. In general, urban areas have increased in temperature more
than non-urban areas. Given the historical trend in Europe towards increasing urbanisation,
ever more people and assets are being put at risk from suffering the
consequences of this temperature rise. Regions also contribute to their own
climate, in the sense that, for example, the temperature in cities is partly
the result of land use and land cover, which implies that the climate change
they experience is, to some extent, within their control.
Together exposure and sensitivity determine
the potential effect of climate change on a region. Regions, however, also
differ in their capacity to adapt to climate change and counteract its effects,
and any assessment of a region’s overall vulnerability to change has to take
this into account as well.
The ESPON Climate project[1] provides such an
assessment, based on projections of climate change and climate variability
generated by the CCLM climate model.[2]
Given these projections, the potential effect of climate change has been
assessed for each EU region on the basis of its exposure and sensitivity to
change and its capacity to adapt, as gauged from several indicators of its
physical, environmental, social, economic and cultural features (e.g. projected
changes in the number of summer days above 25°C coupled with the number of
people of 65 and older living in hot parts of urban areas and the proven
ability to cope with heat). 
The results highlight the large variations
in the potential impact of climate change on regions. While, as might be
expected, ‘hot spots’ are mostly located in the South of Europe, other types of
region (such as mountainous or densely populated coastal ones) are also
particularly affected because of a rise in sea levels or their economic
dependence on summer and/or winter tourism. Some areas in northern Scandinavia are affected as well, mainly because of the sensitivity of the environment and
the vulnerability of infrastructure to floods. 
The general north-south divide in the
effects which emerges, however, not only reflects the impact of climate change
itself but also the greater capacity of Scandinavian and Western European
countries to adapt to it. A medium-to-high impact can, therefore, be expected
in large parts of South-East Europe as well as the Mediterranean regions.
Map
1: Potential vulnerability
from climate change

2.1.    The EU needs to reduce its
greenhouse gas emissions to reach the 2020 targets

The EU has taken a number of steps to reduce
greenhouse gas emissions while at the same time developing adaptation
strategies to help strengthen resilience to the inevitable effects of climate
change. It has, in particular, encouraged moves towards an energy-efficient,
low carbon economy by setting ’20-20-20‘ targets for 2020 – i.e. reducing
greenhouse gas (GHG) emissions to 20% below 1990 levels[3], raising the share of
EU energy consumption produced from renewables to 20% and improving energy
efficiency by 20%. These are now included as headline targets in the Europe
2020 strategy. It has also set a further goal of progressively reducing EU GHG
emissions by 80-95% of 1990 levels by 2050.[4]

EU initiatives to reduce GHG emissions include
the EU Emissions Trading System (ETS), a market instrument for allocating and
exchanging emission quotas. This is complemented by the Effort Sharing Decision
under which Member States have adopted binding annual targets for reducing
emissions from housing, agriculture, waste and transport (other than aviation)
which are not covered by the ETS and which account for around 60% of the EU's
total emissions. The national targets which relate to the period 2013-2020 are
differentiated according to levels of GDP per head, ranging from a 20%
reduction in emissions (compared to 2005) in the most developed Member States
to a 20% increase in the least developed. 
Cohesion policy cannot directly contribute to
the ETS. But  it can play a significant role in reducing GHG emissions in
sectors included in the "Effort Sharing Decision". For instance,
Cohesion policy supports initiatives to insulate public building and so reduce
GHG emissions in the housing sector. It also provides funding for cleaner
public transport and more efficient management of waste both of which should
help to lower GHG emissions.
The reduction in GHG emissions in the areas
covered by the Effort Sharing Decision has been substantial in some Member
States (Figure 34). Between 2005 and 2011, it amounted to 16% in Hungary and over 14% in the UK. In a number of EU12 countries, however, the reduction has been more
modest, reflecting their high rate of economic growth up until the crisis.
Emissions, moreover, have increased significantly in Poland and Estonia (by 9% in both). Since 2008, however, the economic downturn has generally served to
moderate emissions. 
The distance from the various national targets
also varies markedly between countries. Several countries have already more
than achieved their target, such as Hungary or Romania, which committed
themselves to limiting emissions to no more than 10% and 19%, respectively,
above 2005 levels, and where they have actually declined. In other countries,
the target has not yet been reached but emissions have started to fall, such as
in Sweden, where the target was a reduction of 17% and emissions have fallen by
10% relative to 2005. In Malta, on the other hand, emissions have risen above
the target. Luxembourg, Denmark, Ireland and the Netherlands are furthest from
their targets, while the UK (which needs to reduce emissions by a further 2%)
and Austria, Belgium and France (which need a further 4% reduction) are
closest.[5]

Figure
1 – Change in greenhouse
gas emissions outside the Emissions Trading Scheme, 2005-2011 and Europe 2020
targets
Source: European Commission, DG CLIMA.
Box:
Production-based and consumption-based emissions
In
greenhouse gas emissions accounting, the level of emissions can be calculated
on the basis of either production or consumption. Production-based emissions
are calculated from the fossil fuel usage in various types of activities (e.g.
industry, agriculture, energy). Consumption-based emissions account for the GHG
generated when producing the goods and services which meet domestic final
demand in a country (i.e. household consumption, government consumption, and
investment), regardless of which country actually emitted the substances
concerned.[6]
For a given Member State, production-based
and consumption-based levels of emissions can be quite different. For instance,
production-based emissions can be low for a country in which
few polluting activities are located while its consumption-based emissions could be high if it imports goods
and services the production of which generated large amounts of greenhouse gases.
This is illustrated in the following graph
in which  production-based emissions are plotted against consumption-based
emissions for each EU-27 Member State. While there is an obvious positive relationship
between the two types of emission, it is far from one to one. For example, in
Luxemburg production-based emissions are close to the EU-27 average but
consumption-based emissions are the highest in the Union. Conversely for Denmark, production-based emissions are very high but consumption-based emissions are much
smaller. It is, nevertheless, the case that in general, highly developed Member
States record the highest levels of emission on both a production and consumption
basis.
Source: JRC-IPTS

2.2.    The EU needs to increase the use
of renewable energy to reach the 2020 targets

The EU has agreed to
source at least 20% of its final energy consumption from renewable energy by
2020. Under the Renewable Energy Directive, Member States have committed to
increasing the share of renewable energy in energy consumption by 2020 to
targets ranging from 10% in Malta to 49% in Sweden. 
The share is already large in some Member
States, amounting to almost 51% in Sweden and around 36% in Latvia (Figure 35), though  it is small in others, such as Malta, and Luxemburg, where it is less
than 4%. Renewables are expected to play an increasing role not only in
supporting the transition to a low carbon economy but also in improving energy
security. 
Member States also vary widely as regards the
present share of renewables in relation to their target. The UK, France and the Netherlands need to increase the use of renewables by almost 10 percentage points
or more to reach their targets. On the other hand, three countries,  Bulgaria, Estonia and Sweden, have already reached their targets, and Romania, Lithuania, Austria and the Czech Republic are close to reaching them. Considerable efforts remain to
be made in a number of Member States reach their targets. There is concern,
however, that the currently low price of fuel, and carbon in general, does not
provide a sufficiently strong incentive to invest in renewable energy. This is
partly due to the fact that, because of the slowdown in economic activity
triggered by the crisis and the resulting fall in emissions, the ETS has experienced a growing surplus of allowances. Moreover,
in the longer term, this could reduce its ability to meet more demanding
emission reduction targets in a cost-effective way. The Commission has
therefore taken the initiative to postpone the auctioning of some allowances.
Figure 2 – Share of renewable energy in gross final
energy consumption,
2006, 2012, target 2020 (% of total gross final energy consumption)
Source: Eurostat
The largest sources of renewable energy in the
EU are biomass and hydropower (which in 2012 produced respectively around 83 and 29
million tonnes of oil equivalent - Mtoe), followed by wind power (17.7 Mtoe), biogas (12 Mtoe) and solar energy photovoltaic, 5.8 Mtoe and geothermal, 5.7 Mtoe. While hydropower and geothermal are restricted to particular locations, wind and solar power, biomass and heat pumps can be used  more
widely , though the potential to produce energy from either varies markedly between
regions. The ability to make full use of renewable energy potential also
depends on the existing regional transmission, distribution and storage
infrastructure, as well as the pattern of demand[7].
Larger shares of renewable energy supply, which in many cases provides intermittent
power, will require improved infrastructure and solutions to its effective
integration into the network. 
Coastal regions generally have a much greater
potential than others for producing energy from wind power, especially those
around the North Sea or the southern part of the Baltic. Some islands in the Mediterranean have high potential too. The cost of producing energy from wind power is also
lower where the wind is consistently strong enough to produce electricity. 
The most suitable areas
for using solar power are in the southern and western
parts of Europe, where the sun is at its strongest (Map
60, which indicates the suitability of areas for solar power[8]). Northern, central
and eastern Member States are less suitable, though solar panels can be
installed on the roofs of buildings of all types, industrial and commercial as well as
residential, to provide power directly to users without
effectively taking up space. While large-scale
photovoltaic systems, or solar
farms, require more space, they produce energy more
efficiently and their impact on the environment can be reduced by locating them
on unused, or low-yield, farm land.
Map 2 Average suitability for photovoltaic
systems
Box - The
territorial dimension of the Climate change and energy package
The climate
change and energy package takes specific account of the level of economic
development of Member States in setting the targets for GHG emissions outside
the emissions trading mechanism and for renewable energy. 
Renewable
energy sources contribute to diversifying the energy supply in the EU and to
improving the competitiveness of some regions by stimulating the growth of new
industries and helping to create jobs and export opportunities. In addition,
the proposed energy projects of common interest, with an allocation of EUR 5.1
billion as part of the Connection Europe Facility, can potentially make an
important contribution to improving energy security and competitiveness in
areas where commercial viability is not attractive enough.
Investment
in energy efficiency, such as in reducing the energy used by heating systems,
can also bring substantial benefits to those living in cities by improving air
quality. The revised Energy Performance of Buildings Directive (EPBD) adopted
in 2010, which is not yet fully implemented, should further improve air quality
in cities by cutting energy consumption.
In the case of urban transport, the
regulations establishing performance standards for light duty vehicles have led
to substantial reductions in GHG emissions, reflected in a decline of average
CO2 emission of new vehicles from 172 grams per km in 2000 to 135.7
grams in 2011. Such a reduction also benefits public health and ecosystem health
by cutting air pollutants such as NO2 and PM10.
Regional and local authorities are
important active stakeholders in the process. The effectiveness of climate and
energy policies depends on the active support of regional and local
authorities, which are responsible for building permits and spatial planning.
The authorities are also responsible for public buildings, and in some cases
for public housing, which need investment to increase their energy efficiency. 
The White Paper on adapting to climate
change[9]
champions a local, place-based approach to adaptation, which in practice means
local authorities cooperating to design and implement joint sustainable climate
and energy policies for sustainable transport, improving energy efficiency in
buildings and district heating, developing renewable energy sources and
distributed energy generation.
Smart Cities and
Communities European Innovation Partnership (SCC) is intended to increase
inter-linkages between energy production, distribution, and use; mobility and transport;
and information and communication technologies (ICT). In addition, the Covenant
of Mayors is a European-wide movement supporting local and regional authorities
in achieving the European 2020 climate and energy policy objectives. As well as
saving energy, the aim of the signatories is to help create skilled and stable
jobs; a healthier environment and quality of life; increased economic
competitiveness and greater energy independence. To date there are more than 5,000
signatories and over 200 supporting bodies, meaning that it effectively covers
nearly 170 million people in Europe.

2.3.    EU needs to adapt to more
frequent and disastrous natural hazards

The number and costs of disasters caused by
natural hazards[10]
has increased in Europe in recent years. This is due not only to climate change,
which  is likely to increase the frequency, intensity and duration of
weather-related events in future years, but also to human and economic activity
including a higher take-up of land[11].
The most frequently-occurring natural hazards
in the EU are heat waves, storms, earthquakes, floods, droughts and forest
fires. Heat waves have caused by far the largest number of human casualties
over recent year.[12]
Extremes of high temperature[13]
have become more frequent and are likely to become even more frequent and
intense with climate change. 
To measure the potential impact, an urban heat
stress indicator has been developed (by the JRC in Ispra) for a number of
cities in the EU which takes account of both the natural risk and the capacity
to mitigate it.[14]
This shows that the highest potential impact is in the Mediterranean regions in
 Spain, southern France, Italy and Greece, which tend to have a low capacity to
adapt. This applies equally to cities in Eastern Europe, though these are much
less exposed to heat. Regions in central and northern Europe, on the other
hand, have low risk and high capacity to adapt. 
The rise of temperature in cities is not only
due to global warming but also to the way they have developed. In particular,
increases in temperature also depend on land use in the city, the energy
efficiency of the buildings and the main modes of transport. These are aspects
which fall directly under the remit of Cohesion policy. 
Forest fires are frequent in Europe, with an
average of 70,000 fires occurring every year. Over recent years, forest fires
have destroyed over half a million hectares of forest and other wooded land
annually, mainly in the Mediterranean. The largest fires have occurred in Portugal (in 2003 and 2005), Spain (2006) and Greece (2007). While forest fires at some level are
important for the long-term sustainability of forests, they are also a cause of
human casualties, though much less so than heat waves, and lead to substantial
economic loss – amounting to an estimated EUR 7 billion over the period
1998-2009 according to the EEA. 
Pressure on water resources has increased in
the EU and large areas are now more frequently affected by water shortages and
droughts, not only in the drier areas but also in more humid parts. Droughts
can have severe effects on agriculture, tourism and energy as well as on
freshwater and related ecosystems as they often reduce river flows, lower lake
and groundwater levels, dry wetlands and lead to a deterioration in the quality
of water.Also, oceans and seas around Europe are increasingly suffering from
the impacts of climate change, affecting in turn sectors such as fisheries,
aquaculture, and tourism. 
According to various climate projections, the
frequency of water shortages and droughts is likely to increase significantly
in the future as a result of climate change and the resulting higher average
temperatures. Such events are also expected to extend beyond southern Europe increasingly affecting other parts of the EU. Moreover, demand for water in dry
periods often exceeds availability and the need to ensure adequate water
supplies to vulnerable ecosystems is frequently neglected. 
Together with storms, floods cause the largest
economic losses. Many parts of the EU areas have been affected by floods in
recent years, such as the Elbe Basin, the French and Italian Alps, the Po
Valley, the banks of the Rhine in Germany, France and the Netherlands, regions
of the low Loire in France and Mecklenburg-Vorpommern as well as western Poland.
Several regions in Slovakia and the Czech Republic are also particularly
exposed to the risk of floods. 
River flooding can be particularly damaging in
urban areas to both infrastructure and human life. The impact of floods on
major cities in the EU has been assessed by the JRC-ISPRA, using an indicator
which takes account of both the risk of floods and the capacity of cities to
mitigate and recover from them.[15]
The indicator shows a wide variation in exposure to floods between cities, in
part depending on their location vis-à-vis major waterways. The most
vulnerable spots, where a high risk of flooding is combined with low capacity
to adapt, are in a number of regions in Romania, Poland, Latvia, Lithuania, Portugal and southern Spain.
The risk is expected to increase in the future
in many coastal areas because of a rise in sea levels and temperatures. This is
so for those at sea level, or less than 5 meters above this, such as regions
along the Dutch coast. 
In the light of this, policies for preventing and
managing risk are essential to ensure that development, and economic growth,
are sustainable.

3.     Shifting
to more sustainable transport can increase energy efficiency and improve air quality

The EU has taken action to improve energy
efficiency through the 2011 Energy Efficiency Plan and the Energy Efficiency
Directive. Energy efficiency is mainly to do with reducing energy use in
buildings and transport, which in 2010, were
responsible for 41% and 32%, respectively of total energy consumption in the EU. 
Improving the energy
efficiency of housing and buildings comes through applying both current
technology and new innovations. Energy efficiency of
buildings can be improved, in particular, by adding insulation and improving heating
systems, though again, there are large variations across the EU in this regard,
with Member States in Central and Eastern Europe, which could potentially
contribute substantially to energy savings in the EU, lagging behind.

3.1.    Improving
accessibility and energy efficiency 

One of the objectives of the EU’s common
transport policy is to increase energy efficiency and to ensure that the
transport system is a sustainable one by 2050. In order to achieve this, three broad
goals have been set: develop and deploy new and sustainable fuels and
propulsion systems, (2) optimise multimodal logistic chains, including a shirt
to more energy efficient modes and (3) increase effiency with the use of
information sysstems and market-based incentives. . Reducing the distance
travelled while maintaining or improving accessibility is a means of achieving
all three of these goals
Technological advance is another way of
increasing energy efficiency. The adoption of new technologies can increase
fuel efficiency. A shift to more energy efficient modes of transport can help
to achieve all three goals, while an improvement in the transport network can
facilitate such a shift and at the same time might reduce congestion. 
When people use transport, whether a car, bus,
train or bicycle, they usually do so to travel to, or to access, a
specific destination. Accordingly, transport analysis needs to distinguish how
far people travel from accessibility (getting where they want to be). In some
cases, distances can be reduced while accessibility is increased. When people
and destinations are close to each other, as is often the case in cities, the
average distances travelled tend to shrink. For
example, in the Netherlands in 2011, people living in a town or city travelled
an average of 26 km a day as against 30 km a day for those not living in an
urban area. 
Due to the shorter distances, walking and
cycling are more attractive options in towns and cities than in other areas.
There is also a higher demand for public transport which makes it more cost
effective and energy efficient, so people use it more and their cars less. The
Dutch example also shows that people living in a very urban environment walk
more (0.95 km as against 0.6 km), use public transport more (5.6 km as against
1.9 km) and use the car less (16 km as against 24 km) than those living in
other areas (Statistics Netherlands 2013). These differences are reflected in
the regional figures, with Amsterdam, Rotterdam and Utrecht having the shortest
distances travelled and the lowest car use in the Netherlands. Although such
detailed data are not available for the EU as whole, the use of more energy
efficient modes of transport seems to apply in other EU cities too[16]. Cars tend to account for a particularly large share of travel
outside cities because public transport is less efficient and distances make
walking and cycling less feasible[17].

In order to compare the relative importance of
inland[18]
modes of transport between countries, the data can be normalised by expressing
the level of passenger distances in relation to population. Luxembourg and France registered the longest distances travelled in 2011, each of these countries
averaging more than 15,000 passenger-kilometres per inhabitant (Figure 36). By
contrast, EU 12 Member States have the smallest amount of travel, with Romania and Malta having the lowest figures. These figures, however, reflect a range of factors,
such as, the level of GDP and income, infrastructure endowment, the importance
of commuting, the proximity of services to population, access to high-speed rail links and the existence of international
transport corridors running through the country. 
Figure 3 - Modal split of Passenger Transport on Land by
Country - 2011
Between 1995 and 2011 there was a marked
increase in the use of cars  in many of the Member States that have joined the EU since , particularly in Lithuania, Poland, Slovenia Estonia and Bulgaria, There was also a substantial increase in the use
of cars in Greece (Figure 35). This increase in car use has been accompanied by
a significant reduction in the use of public transport in the EU-12, especially
in Slovakia.
By contrast, the use of cars declined in in the
 UK and the Netherlands, in the former accompanied by an increase in rail
travel. 
Figure 4- Modal split Change of Passenger
Transport on Land by Country,
1995 - 2011
Cars accounts for a sizable proportion of
passenger transport in all Member States for which data are available, considerably
larger than rail, and buses and coaches. In 2011, cars accounted for 84% of all
inland passenger km travelled
in the EU, though the figure varies markedly between Member States (from 91% in Lithuania to 64% in Hungary) reflecting differences in infrastructure and geography (Figure
38). 
Figure 5 Share of passenger travel by mode of transport in
EU Member States, 2011
Buses accounted for 9% of passenger km
travelled on average, the share varying from 3% in the Netherlands to 25% in Hungary, while trains accounted for just 7%, though the figure varies according to the state of the rail network and its
extent. In France, Austria and Sweden, which have fast
and frequent trains, around 10% of travel is by rail,
while in Greece, Estonia, Lithuania, where the network is limited and trains
slow and not very frequent, relatively few journeys are made by train.
Figure 6 Share of freight by mode of transport in EU Member
States, 2011
Most freight transport in the EU (75%) is by
road (Figure 39). In some countries, such as Greece and Spain, the large share of freight carried by road is partly due to the lack of inland
waterways and a limited rail network (other than high-speed). In Latvia and Estonia, on the other hand, over 50% of freight goes by rail, partly reflecting imports
by this means from Russia. Inland waterways are used more than elsewhere to
transport goods in Romania, Netherlands and Belgium because of navigable rivers
and canals.
Strategies for improving the efficiency of transport
need to differ between regions. In Western regions as well as in some of the more
developed parts elsewhere, there is already a well-developed road network. Policies
here should therefore focus on shifting to more energy efficient modes of
transport. In many less developed regions, on the other hand, a good standard road
network and connections to the rest of the EU are still lacking.

3.2.    Large cities provide better access
to public transport

Public transport varies from city to city
across the EU in terms of the scale and frequency of service and the forms it
takes[19]. Up until recently, it was difficult to compare the public
transport available in different cities because there was no common definition
of a city and data on public transport was limited. These difficulties are
starting to be overcome[20]. 
The EU-OECD definition, referred to earlier in
this report, provides a harmonised way of delimiting urban centres, cities and
their commuting zones, while more and more public transport operators now give
free access to their data in a common format (GTFS, as used by Google maps).
These data can then be combined with high-resolution population distribution
data[21] and a digital map of streets to produce the first harmonised
analysis of access to public transport in European cities. 
The analysis distinguishes two modes of public
transport:
·   Medium-speed modes: buses and trams
·   High-speed modes: metros and trains
Ease of access is defined for each mode:
·   a five minute walk for medium-speed modes 
·   a ten minute walk for high-speed modes.
Frequency of service is defined on the basis of
the average number of departures an hour between 7 am and 8 pm on a normal
weekday: 
·   very high: access to more than ten
departures an hour for both medium- and high-speed modes;
·   high: access to more than ten departures an hour for one mode but
not both;
·   medium: access to between four and ten departures an hour on one or
both modes, but no access to more than ten departures and hour;
·   low: access to less than four departures an hour for one or both
modes, but no access to more than four departures an
hour
The proportion of people that have easy access
to public transport, broken down by frequency of departures, can be compared
across a number of European cities. In 12 out of 14
large urban centres examined (Figure 40), between 60% and 84% of the population
had access in 2012 to a high frequency service. The proportion of population
with very high access was more variable, ranging from over 30% in five centres
and less than 10% in three. Dublin has the smallest proportion with access to a
high frequency service (38%), much less than Stockholm (71%) or Brussels (84%), which are of similar size. 
The Hague and Amsterdam also score relatively low on this measure, though in Amsterdam the construction
of a metro should increase the proportion substantially. Public transport
services in the Dutch cities have to be seen, however, in the light of the extensive
use of bicycles, which reduces the demand for them. The urban centre of Manchester, which covers most of Greater Manchester, has a small proportion of the population
with very high access given its size.
In 9 of the 14 mid-sized urban centres (Figure 41),
access to a high frequency public transport service in 2012 varied between 12%
and 60% of the population, the proportion with very high access not exceeding
7% in any of them. In general, therefore, public transport services are much
more frequent in larger urban centres.
Figure 7 - Access to public transport in large
European cities, 2012
Figure 8 - Access to public transport in mid-size
European cities, 2012
 Box: Improving access to public transport in Athens. Since the 1990s, over EUR 4 billion has been spent on the Athens Metro rapid transit system, which serves the Athens conurbation and parts of East Attica, much of it financed under Cohesion policy (by the ERDF and Cohesion Fund as well as by EIB loans) with the main aim of reducing traffic congestion[22]. Before the metro, public transport consisted only of buses and the Athens-Piraeus electric rail line. The metro has improved the quality of life in Athens considerably, reducing traffic congestion and smog levels and cutting journey times markedly. It has also helped to reverse the decline in public transport use, the number of passengers increasing by 50% between 1992 and 2008. Prior to the construction of lines 2 and 3 of the metro, only 8% of the population in the Athens urban centre had access to a very high frequency public transport service, much less than in Berlin, Stockholm, Copenhagen, Brussels or Marseille (30% in each). This was increased to almost 20% after the construction of the lines. 
 Box on Urban mobility package A successful European transport policy, cannot ignore the urban dimension. Cities are important nodes of the European transport system and most trips originate or end in urban areas. Furthermore, many of the negative effects of transport (like congestion and pollution) occur mainly in urban areas. According to the latest Eurobarometer Survey[23], half of all Europeans use a car every day (50%), which is more than the proportion who cycle (12%) or use public transport (16%) combined. On the other hand, a substantial majority of Europeans believe that air pollution (81%), road congestion (76%), travelling costs (74%), accidents (73%) and noise pollution (72%) are serious problems in cities. With the Urban Mobility Package, the Commission is reinforcing its support for urban transport in the 2014-2020 programming period. Urban mobility planning is intimately linked to achieving EU policy objectives for a competitive and resource-efficient European transport system, but the organisation of urban mobility is primarily a responsibility of authorities at the local level. For many years, EU initiatives on urban mobility have primarily sought to support efforts at city level by taking action in areas with clear EU added value. The present  package invites Member States to ·   conduct a careful analysis of the present and future performance of urban mobility in the light of key EU policy goals; ·   ensure that sustainable urban mobility plans are developed and implemented; ·   review the technical, policy-based, legal, financial, and other tools at the disposal of urban planning authorities. The central element of the package is the "Together towards competitive and resource-efficient urban mobility" Communication, which is accompanied by an annex that sets out the concept of sustainable urban mobility plans and by four staff working documents on urban logistics, urban access regulations, deployment of ITS solutions in urban areas and urban road safety. 

3.3.    Congestion is high in several of
the large EU cities

Efficiency of transport networks is a main
priority for transport policy at EU level as expressed in the European
Commission's Roadmap to a Single European Transport Area – Towards a
competitive and resource efficient transport system[24]. The existing routes in the road transport network vary
significantly in terms of the volume of traffic carried and, consequently,
capacity utilisation and congestion[25]. 
Congestion is estimated to cost over EUR 110 billion a year in the EU25. It also has
a range of indirect adverse effects, such as increased fuel consumption, air pollution and noise as well as
affecting the quality of life and access to shops and other services[26]. Congestion is severe in several large cities (Map 61). In Brussels, Milan, Lille and Manchester, over 25% of high-speed roads are congested. This could be reduced by the introduction of
congestion charging – which the OECD has recommended in
several countries – to encourage people to adjust the time they travel, the
route they take and/or the mode of transport they use. 
Map
3 Congestion index on the
high speed road network, 2012

3.4.      Air
quality can still be improved in many places in the EU

Air quality is a key aspect of well-being that
can affect human health and the environment. In the EU, emissions of many air
pollutants have declined substantially over the past decade, reducing exposure
to substances such as sulphur dioxide (SO2), carbon monoxide (CO)
and lead (Pb). However, some air pollution problems persist in a number of
regions in the EU where air quality is regularly lower than the standards
specified in EU Directives. This is especially true of cities, where the
majority of people live.
At present, airborne particulate matter (PM10)[27], ground-level ozone (O3)
and nitrogen dioxide (NO2) remain the most problematic pollutants in
terms of harm to health. Despite the emission of many pollutants from industry,
agriculture, transport and housing being regulated by EU Directives[28], many Member States do
not comply with air quality limits which are intended to be legally binding.
Measured concentrations of PM10 and O3 have shown no
significant reduction in recent years. The Air Quality Guideline level for PM10
set by the World Health Organisation (WHO) of 20 μg/m3 is regularly
exceeded all over Europe in rural as well as urban areas. In many EU cities, PM10
concentrations have not changed since 2000 or so.
Regions most affected by high PM10
concentrations are those in the Po Valley in Italy, in southern and central Poland, the Czech Republic, Slovakia and Bulgaria (Map 62). High concentrations of O3
occur mostly in the southern EU, notably in Northern Italy, where the target
level is exceeded for 25 days a year or more (see map) ().
Although the EU has not reached its interim
environmental objective set to protect sensitive ecosystems from acidification,
the area affected by excessive acidification from air pollution was reduced
considerably between 1990 and 2010, as a result mainly of previous measures to
mitigate SO2 emissions. The area of sensitive ecosystems in the EU
affected by excessive atmospheric nitrogen, however, diminished only slightly
between 1990 and 2010[29],
and ambient O3 concentrations still reduce vegetation growth and
crop yields.[30]

 Map 4 Annual mean concentrations of PM10, 2011 || Map 5 Ozone concentration, 2011 
Other sources of
pollution are also monitored. In particular, the EU has tackled emissions of mercury
which is a global pollutant (i.e. circulating between air, water, sediments,
soil and living organisms) causing significant harm to human health, by launching
a strategy in 2005 which included 20 measures to reduce emissions, cut supply
and demand and protect against exposure, especially to methylmercury found in
fish. 

4.     Making cities more attractive
can boost EU Resource Efficiency

Cities are
significantly more efficient in in terms of energy use and land use than other
areas. Energy consumption by private households in cities tends to be lower
because a larger proportion of people live in apartments or terraced housing
which are more efficient in terms of heating than freestanding houses. For
example, in the Netherlands, gas and electricity consumption per head is twice
as high in freestanding houses than in apartments. The difference is big enough
to show up even at the regional level. The NUTS-2 regions in which Amsterdam and Rotterdam are located accordingly have the lowest gas and electricity consumption
per head in the Netherlands[31].


4.1.      Cities use land more
efficiently

An even stronger example of the efficiency of
urban living is the impact on land use. On average, urban areas use only around
a quarter of built-up land (i.e. land with a building on it) per person living
there than rural or intermediate areas. This is shown by the JRC using
high-resolution satellite imagery to detect built-up
areas, whether the buildings in question are residential, commercial,
industrial, agricultural or a mix of different types (Table 16 and Maps 64 and 65).
This pronounced difference applies to both the EU-15 and the EU-13.
Table
1 Built-up area per
inhabitant, 2012 (in sq km per million inhabitants)
   || Predominantly urban || Intermediate || Predominantly rural 
 EU-28 || 97 || 230 || 368 
 EU-15 || 94 || 221 || 372 
 EU-13 || 126 || 260 || 362 
Source: JRC and DG REGIO calculations
[1]
      See ESPON, 2011, Climate Change and Territorial Effects on Regions and
Local Economies in Europe, Applied Research 2013/1/4. http://www.espon.eu/main/Menu_Projects/Menu_AppliedResearch/climate.html

[2]       CCLM is a non-hydrostatic unified weather forecast and
regional climate model developed by the COnsortium for Small scale MOdelling
(COSMO) and the Climate Limited-area Modelling Community (CLM). 
[3]       The EU also offered to reduce emissions by
30% if other major emitting countries committed to making their fair share of
reductions.
[4]       Note that these targets are set on a production basis which means
emissions arising from within the borders of the EU. However, with
globalisation, an ever-increasing proportion of emissions is emanates from
regions outside the EU while being a result of EU imports. Indeed, since 1990,
net-emission transfers from the Annex 2 countries of the Kyoto Protocol to
non-Annex 1 countries have increased fourfold. For details see:
 http://www.pnas.org/content/early/2011/04/19/1006388108.abstract

[5]       GHG emissions are closely related to economic activity. The
current high level of uncertainty about future economic trends, therefore,
makes it difficult to judge the capacity of the Member States to meet their
2020 targets on the basis of their present level of emissions, even in the case
of those where emissions are already below the target.
[6]       See European Commission, JRC-IPTS, 2012, Global Resources
Use and Pollution, Volume 1 / Production, Consumption and Trade
(1995-2008). http://ftp.jrc.es/EURdoc/JRC71919.pdf
[7]       Another consideration would be the environmental effects of
the renewable energy. For example, combustion of biomass leads to emissions of
PM which is carcinogenic, so it should be accompanied by strict emission
limits.
[8]    Suitability takes into account factors both restricting
the development of solar power and supporting it. The criteria include high
solar radiation, smooth slopes, distance from densely population settings,
proximity to roads and electrical grids. Protected areas, forests, water bodies
and land already developed are defined as not being suitable.
[9]       European Commission, 2009, White paper - Adapting to
climate change: towards a European framework for action, COM/2009/0147
final.
[10]     See SWD(2014)134 Overview of natural and man-made disaster
risks in the EU
[11]     See EEA, 2010, Mapping the impacts of natural hazards and
technological accidents in Europe - An overview of the last decade, Technical
Report No 13/2010.
[12]     For the period 1998–2009, the EEA reports 576 disasters due to
natural hazards causing almost 100,000 fatalities, of which .over 77,500 were
due to heat waves. Ibid. 
[13]     Extreme temperatures are relative to the usual weather
conditions in a given area, so there is no universal definition of a heat wave.
There are, however, proposals for a generic definition – e.g. the European
Climate Assessment and Dataset project defines a warm spell as a period of at
least six consecutive days in which the mean daily temperature exceeds the 90th
percentile of the average daily temperature in the 1961–1990 period. The World
Health Organisation’s ( EuroHEAT project proposed a similar definition of a
heat wave as 'a period when maximum apparent temperature and minimum
temperature are over the 90th percentile of the monthly distribution for at
least two days' (see EEA, 2010).
[14]     Lung T., Lavalle C., Hiederer R., Dosio A. and L. Bouwer, 2013,
A multi-hazard regional level impact assessment for Europe combining
indicators of climatic and non-climatic change, Global Environmental Change
23: 522-536.
[15]     Lung T., Lavalle C., Hiederer R., Dosio A. and L. Bouwer, 2013,
A multi-hazard regional level impact assessment for Europe combining
indicators of climatic and non-climatic change, Global Environmental Change
23: 522-536.
[16]     TERM 2013 EEA
[17] See also ESPON, 2013, TRACC-Transport
Accessibility at Regional/Local Scale and Patterns in Europe.
[18]   It should be underlined that the analysis above refers only to
inland transport by car, bus or train and that a significant proportion of
international passenger travel, and in some countries national travel, is
accounted for by maritime and air transport (EUROSTAT Pocketbooks, Energy,
transport and environment indicators, 2011 edition)
[19]       European
Environment Agency,
2012, A closer look at urban transport, TERM 2013: transport indicators
tracking progress towards environmental targets in Europe, EEA Report, No
11/2013, Publications Office of the European Union, 2013, ISBN
978-92-9213-413-6, doi:10.2800/94848
[20]       Dijkstra
L. and Poelman H. 2014, Access to public transport in European Cities, .
Regional Working Paper, Directorate-General for Regional and Urban Policy,
European Commission. 
[21]          Using 100m population grids, neighbourhood or enumeration
areas and the Urban Atlas, a new European collection of urban land use maps of
all European agglomerations. 
[22]     European
Commission, 2009, Good practice in urban transport – Athens Metro, Ex
post Evaluation of cohesion policy programmes 2000-2006 co-financed by ERDF
,Work Package 5A: Transport, DG REGIO
[23]       European
Commission, 2013, Attitudes of Europeans towards urban mobility, Special
Eurobarometer 406, Survey co-ordinated by the Directorate-General for
Communication 
[24]       European
Commission 2011, White Paper: Roadmap to a Single European Transport Area,
COM(2011)144.
[25]          European Commission – JRC IPTS, 2012, Measuring Road
Congestion, Panayotis Christidis, J. Nicolás Ibañez Rivas, Luxembourg:
Publications Office of the European Union, EUR – Scientific and Technical
Research series .
[26]     OECD-ECMT, 2007, Managing Urban Traffic Congestion, ISBN
978-92-821-0128-5 
[27]     PM10 (PM2.5) is
particulate matter with an aerodynamic diameter of 10 (2.5) μm or less,
suspended in the air. While EU Directives impose limits on the concentration in
terms of PM10, concentration in terms of PM2.5
is not regulated, despite of the fact that these particulates
are even more dangerous to human health since they penetrate deeper into the
lungs.
[28]     Pollutant emissions: Directive 2010/75/EU on industrial
emissions and Directive 2001/81/EC on national emission ceilings. Ambient air
quality: mainly Directive 2008/50/EC. 
[29]     Nitrogen (N) compounds and ammonia (NH3) are now the principal
acidifying components in the air. In addition to its acidifying effects, N also
contributes to the excess supply of nutrients in terrestrial and aquatic
ecosystems, leading to changes in biodiversity.
[30]     Crop losses and the associated economic loss were estimated for 23
horticultural and agricultural crops in 2000 to amount to the equivalent of to
EUR 6.7 billion (see Holland et al., 2006, Development of a framework for
probabilistic assessment of the economic losses caused by ozone damage to crops
in Europe. CEH
Project No. C02309NEW, Report to U.K. Department of Environment, Food and Rural
affairs under contract 1/2/170 1/3/205).
[31] Unfortunately, such detailed data is not
available for the entire EU.
 Map 1 Share of Built-up area, 2012 || Map 2 Built-up area per head, 2012 
The reasons are twofold: a more efficient use
of land by people and businesses in urban areas and more industrial and
agricultural buildings in other areas. Accordingly, the growth of population
and economic activity in cities has a smaller impact on land use than the same
growth elsewhere. 
Large cities use land more intensively than
smaller cities
The same conclusion results from using a
slightly different indicator, that of soil-sealing (imperviousness), which
shows that where population densities are higher, the amount of soil sealed
(i.e. concreted over) per head is smaller. Larger cities, which typically have
higher concentrations of population, therefore, tend to be more efficient than
smaller ones (Figure 42).
Figure
1. Relationship between
population density and sealed soil per head
in larger urban zones, 2006.
Land in the centre of large cities is the most
intensively used
Average population densities per city, however,
tend to mask a great deal of variation. Population density tends to decline the
further away from the city centre an area is located. In the larger EU
capitals, population densities tend to peak within a distance of 3-4 km from
the centre (Figures 43 and 44)[1].

The general pattern can be explained by
economic theory that goes back to von Thünen, who observed that the price of
land, and its corresponding use, varies according to access to the market (the
city centre). The highest return to land use, therefore, tends to be close to
the city centre, where shops and services are concentrated, followed by high
density residential use. Returns to land use decline with the distance from the
centre. 
Despite this general tendency, population
densities in practice differ between cities of similar size. For example, Paris peaks at a density of 520 inhabitants per square km, while London peaks at just
under 300. Madrid, Athens and Berlin peak at 650, 400 and 290, respectively.
Figure
2 Population density
profile of a selection
of large European capital cities, 2006
Figure
3 Population density
profile of a selection 
of mid-sized European capital cities, 2006.
In the medium-sized capital cities, the peaks
tend to be lower. Stockholm, Vienna and Brussels have a peak of between 300 and
400 inhabitants per square km, Lisbon, Dublin, Amsterdam and Budapest, between
200 and 300.
After peaking, population density falls, more
or less abruptly, towards the periphery. This is clearly the case for Paris, Athens, Vienna, Budapest, Stockholm, Brussels and Dublin. Secondary peaks are also
evident in some places, such as in Madrid, Lisbon and Amsterdam, which could be
related to the existence of ‘satellite’ urban centres in the vicinity of the
main agglomeration.
Urban population growth and changing land
use intensities
A new analysis shows how a number of cities
have changed in terms of land use and population between the 1950s and 2006.
The most rapid changes occurred in the 1960s and 1970s which saw high
population growth and an even faster expansion of built-up areas. For example,
in Palermo, the built-up area tripled between 1955 and 1984, while its
population increased by only 26%. In the following two decades, the pattern of change
was different: built-up areas increased by 9% and population shrank by 3%.
In Helsinki, the built-up area almost doubled
between 1950 and 1984, while its population grew by 25%. In the following two
decades, population and built-up area increased by 12% in both cases, leaving
land-use intensity unchanged. 
In contrast, in Vienna, the built-up area increased
by only 15% between 1955 and 1997, while population shrank by 5%. In the following
decade population grew by 7%, while the built-up area increased by only 4%
leading to higher land use intensity.
Comparing the land use intensity of Palermo,
Vienna, Helsinki and Bratislava between the 1950s and 2000s,shows a rapid
convergence of built-up areas relative to population to about 9000 inhabitants
per square km  by the 1980s and very little change since.
The revival of many EU urban centres during the
1990s and 2000s has allowed cities to reclaim brownfield sites and reuse
abandoned buildings, increasing the vitality of city centres without expanding
the built-up area.
[1]       In the majority of the cases, the city centres themselves are
actually not as dense as the immediately surrounding areas. This is due to a
high share of commerce and services, and in some cases as well, depopulated
historical centres.
Map 1 Change
in land use in Vienna, Palermo, Prague and Helsinki, 1950s-2006
 Box The urban atlas shows faster changes in Central and Eastern cities The Urban Atlas provides reliable, comparable, high resolution land use maps for 408 European cities and their surroundings for the reference years of 2006 and 2012[1]. It was created to fill a gap in knowledge of land use in European cities. It uses images from satellites transformed to detailed land use maps to allow land use comparisons not only between cities but also over time and to enable analysis of land use changes to be made so increasing understanding of urbanisation trends. The latest analysis of the Urban Atlas comprises a sample of land use maps (2012) for five European cities with their respective changes in land use over the period 2006-2012. The results for 2012 demonstrate a variation in the intensity of between the five cities, as a result of different spatial patterns, urban forms and development potential. Bratislava seems to use land most intensively, followed by Edinburgh and Prague, while  Munich and Bucharest use land least intensively. In most of the cities, industrial, commercial, public and military units consume half as much land or less as residential areas. This is not the case, however, in Bratislava, where the use of land by the two is much the same. Over the period examined, in most of these cities, built-up areas tended to expand  while at the same time there was growth of population, except in Bratislava (Map 67). The most significant changes in land use during 2006-2012 were in cities in Central and Easter Europe, like Prague and Bucharest, where their rapid growth was associated with a similarly rapid increase in built-up areas. Both faced a marked rise in population and in both, agricultural, forest and other natural areas were reduced to accommodate housing and economic activities. Hotspots of change in land use are more evident than in Bratislava, where new built-up areas were developed close to major transport routes, despite a decline in population. On the other hand, in Munich and Edinburgh, there were only limited changes in land use between 2006 and 2012 and both can be more compact and sustainable. In both cities, wetlands and areas of water were expanded in contrast to the other cities which lost natural environment areas under the pressure of economic activities. Understanding trends in urbanisation and their effects across Europe is therefore crucial for maintaining economic and social cohesion and sustainable development. Urban Atlas is a significant contribution in this regard. 
[1]       The Urban Atlas is a joint initiative between ESA, DG ENTR (Copernicus),
DG REGIO and EEA
Map 1 – Land use changes 2006-2012

4.2.    National
and local policies can shape the location and land use intensity of new
developments by promoting more compact cities

Compact cities can offer major savings in terms
of infrastructure and travel time, so reducing the damaging environmental
effects of built-up areas and high energy consumption. Matsumoto[1] has defined the
following key features of compact cities:
·   Contiguous development patterns: new urban development is typically
located at the fringes of existing urban areas and urban sprawl is avoided.
·   Dense built-up areas: urban land is used intensively, with more
residents and more activities in a given size of built-up area.
·   High levels of accessibility: mass-transit links ensure a high-level
of mobility in the urban areas and a mixed use of land ensures that people
enjoy fast access to services.
These features were taken into account in using
the Land Use Modelling Platform to define two scenarios of future land use[2]: a business-as-usual
one and a compact city one. Both scenarios incorporate estimates of the impact
of Cohesion Policy (based on the RHOMOLO results) and improvements in
accessibility. Cohesion policy support for investment in specific policy areas
is also allowed for (e.g. in R&D facilities, health and education, waste
and wastewater treatment, and urban regeneration). The main difference between
the two scenarios is that in the first no specific urban land use policies are
assumed to be put in place, while in the second a policy in favour of more
compact cities is assumed.
Comparison of the two scenarios indicates many
benefits from developing compact cities. Although in both scenarios, the intensity
of land use continues to fall, the reduction is less in the compact city one,
in which, in addition, there is less urban fragmentation, more infill
development and the emergence of large city centres. In the business-as-usual
scenario, there is more urban sprawl and more use of cars, with consequently
higher energy consumption, illustrating the fact that such a pattern of
development tends to lock people into a car-dependent lifestyle.

5.     Improving
Eco-systems and reducing environmental impacts can make the EU more efficient
and a better place to live
5.1.      Preserving water quality and protecting species and habitats

Water is, of course, a key natural resource
which plays a central role in the functioning of the biosphere and in
supporting all forms of life as well as being vital for agriculture and many
other economic activities. In addition, freshwater and coastal ecosystems serve
a range of regulating functions, such as controlling floods and breaking down
pollutants. They are also essential to the health of marine ecosystems.
However, water resources are under increasing
pressure, often as a result of human activity. Such pressure has different
origins. Changes in land use and the development of economic activities is
often accompanied by pollution and landscape interventions. The latter implies canalisation,
disconnection of flood plains, reclamation of land, the construction of dams,
and the extension of impervious surfaces, all of which alter the hydrological
system. For instance, urbanisation tends to be accompanied by soil sealing and
modifications to the existing sewerage and drainage systems that increase the
risks of flooding and affect habitats and the aquatic environment. Water
reserves are also often subject to extreme abstraction, due, for example, to
the heavy use of water for irrigation by agriculture in some parts of the EU,
especially during the summer, so increasing the risk of drought. Climate change
exerts additional pressure since it is likely to increase the frequency and
severity of both droughts and floods, as well as the temporal distribution of
water availability, especially in areas where gradual snowmelt and water
recharge becomes dominated by rapid thawing and flash floods. This calls for
investment in disaster risk management. 
Performance in preserving aquatic ecosystems
varies considerably across the EU. In a number of regions, many water bodies
have been subject to various kinds of action which have affected their
hydrology (the movement, distribution and quality of water) or their morphology
(through straightening water courses, canalisation or disrupting the connection
to flood plains). This is particularly so for most regions in Belgium, the Netherlands, the Czech Republic, Germany, Poland and Hungary. In France, Sweden, Spain and the UK, water bodies in many regions have also been affected by such
pressure[3]
(Map 68). Many of the changes date back to the early industrial era, such as
the straightening of the Rhine (which occurred between 1817 and 1876), or
earlier, such as the reclamation of land from the sea in the Netherlands. 
 Map 1 Ecological status of main water bodies || Map 2 NATURA 2000 areas, 2012 
The quality of water and the ecological
status of aquatic ecosystems are also affected by pollution-causing nutrient
enrichment in particular. More than half of the surface water bodies (lakes,
rivers, wetlands and groundwater under the surface) in the EU are reported as
not meeting the standards defined by Good Environmental Status (GES)[4] or Good Environmental
Potential (GEP) and require remedial measures being taken to meet the EU Water
Framework Directive objectives.[5]
The worst cases are in the north-west of the EU, where over 90% of water bodies
are in a poor ecological state, mainly as a result of intensive agriculture,
resource-intensive industries and high-population density.
Box - Environmental policy and EU territories
EU environmental policy is pursued through Action Programmes. The 7th
Action Programme, Living well, within the limits of our planet[6], is the most recent. It
draws on a number of recent environmental initiatives, including the Resource
Efficiency Roadmap, the 2020 Biodiversity Strategy and the Low Carbon Economy
Roadmap, in order to reduce environmental disparities across the EU. The policy
is implemented through various means (initiatives, taxes, Directives, charges,
emissions’ trading, green procurement and networks) and has significant effects
on less developed regions as well as on different types of area (urban, rural,
marine, island, mountain etc.) and social groups (such as the unemployed).
The EU environmental policy supports the installation of green
infrastructure[7]
as they can provide ecological, economic and social benefits through natural
means. It can avoid relying on infrastructure that is expensive to build and is
particularly important in cities,[8]
where it can deliver health-related benefits such as clean air and better water
quality. 
Creating green infrastructure can also generate a greater sense of
community and combat social exclusion and isolation as well as opportunities
for connecting urban and rural areas and providing attractive places to live
and work in[9]
together with more jobs [10].
Natura 2000[11]
areas are designated to protect EU most threatened habitats and species, but they
also provide opportunities, for the development of tourism, recreation,
agriculture, forestry sustainable fisheries and aquaculture as well as
nature-based means of controlling floods, adapting to climate change and
producing other ecosystem services, the total benefits amounting to an
estimated EUR 200-300 billion a year.[12]
The establishment of NATURA 2000 is not yet complete but considerable progress
has been achieved with more than 15% of the EU’s territory proposed for
conservation under the network (see map).
Investing in Natura 2000 on land and at sea can also be an opportunity
for advancing cross-border and multi-region cooperation, for example in respect
of the strategy for the Danube strategy or mountain ranges (e.g. the
Alpine-Carpathian Corridor Project has helped greatly to reduce the
fragmentation of the landscape in Austria, Czech Republic and Slovakia through
the construction of ’green bridges’ and the creation of suitable habitats).
The impact of legislative and regulatory measures (e.g. Directives and
EIA standards) on economic and social cohesion is more ambiguous[13]. On the one hand, the
improvement of the environment in less favoured regions increases their
attractiveness for external investors and for tourism and helps to strengthen
their regional identity. On the other hand, the economic and financial
implications of legal provisions can constrain development in both the short
and longer-term.

5.2.    The treatment of urban wastewater
is necessary for ensuring high quality of water

Wastewater also poses significant pressure on
the aquatic environment because of the organic matter and nutrients as well as
hazardous substances and metals that it contains. Nutrient pollution is the
main cause of eutrophication (excessive algae growth and oxygen depletion) and
one of the biggest threats to reach good status of both fresh and marine
waters. Appropriate collection and treatment of wastewater is therefore essential
to preserve the quality of water reserves (from surface water to reservoirs
supplying clean drinking water), bathing water and marine ecosystems. Proper
sanitation is also a basic human right and essential to human health, which has
been recently highlighted again by the first European Citizen’s initiative
(ECI) ‘right2water’[14].
The EU Urban Wastewater Treatment Directive makes it mandatory to collect and
treat wastewater in all settlements and areas of economic activity with the
equivalent of over 2,000 inhabitants.[15]

The level of required treatment depends on the
sensitivity of the area for discharges of waste water. Primary (mechanical)
treatment removes part of the suspended solids and required in areas for which
discharges of waste water do not adversely affect the environment (‘less
sensitive areas’, rather exceptional and due to specific local conditions) ,
secondary (biological) treatment decomposes most of the organic matter but
retains some of the nutrients and is the minimum requirement in all ‘normal
areas’, while tertiary (advanced) treatment removes almost all the organic
matter and required in the ‘sensitive areas’, characterised by increased risks
for adverse effects from discharges or requiring specific protection such as
drinking water abstraction areas. 
[1] OECD, 2012, Compact City Policies: A Comparative
Assessment, OECD Publishing. http://dx.doi.org/10.1787/9789264167865-1-en
[2]     Batista
E Silva F, Lavalle C, Jacobs C, Ribeiro Barranco R, Zulian G, Maes J,
Baranzelli C, Perpiña Castillo C, Vandecasteele I, Ustaoglu E, Lopes Barbosa A,
Mubareka S., 2013, Direct and Indirect Land Use Impacts of the EU Cohesion
Policy. Assessment with the Land Use Modelling Platform. Publications
Office of the European Union; JRC87823.
                                                                                                                                   
[3]       See European Environment Agency, 2012, Water resources in Europe in the context of vulnerability, EEA 2012 state of water assessment, EEA Report
No 11/2012.
[4]       The Water Framework Directive classification scheme for water
quality includes five status classes: high, good, moderate, poor and bad. ‘High
status’ is defined as the biological, chemical and morphological conditions
associated with no or very low human pressure. Assessment of quality is then
based on the extent of deviation from these reference conditions. ‘Good status’
means ‘slight’ deviation from the reference conditions. The definition of
ecological status takes into account specific aspects of the biological quality
elements, for example “composition and abundance of aquatic flora” or
“composition, abundance and age structure of fish fauna” (see WFD Annex V
Section 1.1 for the complete list). 
[5]       Ibid., 
[6]       http://ec.europa.eu/environment/newprg/pdf/7EAP_Proposal/en.pdf 
[7] European Commission, 2013, Green Infrastructure (GI) — Enhancing Europe’s Natural
Capital, COM(2013) 249
[8]       Communication from the Commission to the Council and the
European Parliament on a Thematic Strategy for the urban environment. COM(2005)
718 final.
[9]       Reports, studies and review documents supported by the European
Commission —http://ec.europa.eu/environment/nature/ecosystems/studies.htm.
[10]     See case examples of GI creating jobs in Table 2 of Commission
Services Working Document (SWD(2013) 155 final).
[11]      Natura 2000 is an EU wide network of
nature protection areas established pursuant to the Birds and Habitats
Directives
[12]      According to recent Commission study
"The Economic benefits of the Natura 2000 Network;
http://ec.europa.eu/environment/nature/natura2000/financing/docs/ENV-12-018_LR_Final1.pdf

[13]    European
Commission, 2001, Spatial
impacts of Community policies and costs of non-co-ordination, DG REGIO..
[14]     See COM(2014)177final.
[15]     The concept of population equivalent takes account of the load generated
by the resident population, the non-resident population (largely tourists), and
the industries covered by Art.11 of the Directive.
In general high compliance rates are seen in
the older Member States, with frontrunners such as Austria, Germany and the Netherlands having largely implemented the Directive. However, there are still a few
‘older Member States’ facing serious compliance gaps, including Italy, Spain,
Belgium and Luxembourg mainly in relation to non-appropriate treatment and
consequently causing significant pollution pressures for the areas into which
the concerned discharged waste waters drain. The picture is different for those
Member States that joined the EU in 2004 and later, partially explained because
they are still benefitting from transition periods agreed in the Accession
Treaties. There are still regions where there is no or only partial collection
of waste water. For instance in Member States such as Bulgaria, Cyprus,
Estonia, Latvia and Slovenia less than 30% of the generated waste water is
collected in a proper way (see Maps 11 and 12)[1].
On average, in newer Member States about 40% of the waste water is subject to
secondary treatment, with high rates above 80% seen in Czech Republic, Hungary, Lithuania and Slovakia. Only 14% of the waste water discharged in sensitive
areas in the newer Member States is subject to the required tertiary treatment.
 Map 1: Urban wastewater with more stringent treatment, 2010 || Map 2 Urban wastewater not collected, 2010 

5.3.      Solid waste management
improving but there is still a long way to go in many EU regions

Solid waste affects human health and the
environment as it generates emissions of polluting substances into the air,
soil, surface water and groundwater. It also presents major management
challenges as the quantity of waste produced per person has steadily increased
over time. Recycling and exploiting the energy potential of waste have
therefore become important. 
In 2010, around 4.5 tonnes of waste per person
were generated in the EU-28. Much of this is produced by construction and
demolition, mining, quarrying and manufacturing. Households also generate a
substantial amount of waste, on average 436 kg per person in 2010. Marine
litter, escaping from waste management system, is growing concern.
The total amount of waste generated in the EU
has, however, declined over time. Between 2004 and 2010, the amount of waste
produced per person in the EU fell by 7.1%, though there are wide variations
between Member States. The amount increased by most in Greece, Denmark,
Finland, Portugal, The Netherlands, Sweden, Latvia, Belgium, France and
Luxemburg, while it declined significantly in Malta, Croatia, Austria, Romania,
Hungary, the UK, Ireland, the Czech Republic and Spain. 
Increasingly, waste is recycled or diverted for
energy recovery. From 2004 to 2010, the proportion of waste recycled increased
from 44% to 52% over the same period, while the proportion incinerated with
recovery of energy also rose slightly (from just over 3% to just under 4%). The
increase in recycling has been stimulated by EU and national legislation,
landfill taxes and dumping fees as well as by rising prices for recycled
materials and energy.
In 2010, the proportion of waste deposed of in
landfill is still around 23% in the EU-27[2].
There are, however, marked variations across Member States. More than 70% of
waste is still landfilled in Greece and Estonia while this share is above 40%
in Cyprus, Hungary, Romania, Slovakia and Spain. Less than 5% goes to landfill
in Belgium, Luxemburg Denmark and the Netherlands.
Figure 45 Share of waste landfilled in
selected EU Member States, in 2010
(% of total generated waste, excluding major mineral waste)
Source:
Eurostat

5.4.      Sound ecosystems offer many
vital services

Among their many functions, such offering habitats
for various species of wildlife, ecosystems provide services for people[3]. These range from clean
drinking water to good air quality, and from the pollination of crops to the
regulation of water flows. Ecosystems in coastal and marine regions produce
services by providing food, natural barriers to floods. Forests and woodland
help to regulate water flows, capture carbon and air pollutants from the
atmosphere and prevent soils from being eroded.. Wetlands have the capacity to
improve the quality of water and regulate flows, diminishing the risk of
floods. Ecosystem services are vital for human life, and sustaining their
provision, as well as protecting natural capital, is increasingly recognised by
EU policies as being important for tackling potentially changing conditions in
future years. 
One way of protecting natural capital is the
conservation of biodiversity through establishing nature protected areas, such
as the EU Natura 2000 sites, which are a particular form of green
infrastructure[4].
The services that biodiversity provides, however, do no stop at the borders of protected
areas. Many are produced outside nature sites from other forms of green
infrastructure. Urban forests provide cheap and accessible recreational space
for people. Floodplains, often on grasslands and pastures, provide protection
against floods during periods of high water. Forests and woodland help to
regulate water flows, capture carbon and air pollutants from the atmosphere and
prevent soils from being eroded. This green infrastructure provides a wide
range of benefits to people and is often an economically viable alternative to
man-made solutions. For instance, there are many examples where the
rehabilitation of flood plains and wetlands has proved to be a more efficient
and cheaper means of reducing the risk of floods than the construction of barriers.

The provision of ecosystem services has a
strong regional dimension. It is highly dependent on the local context and
varies with the endowment of natural capital and green infrastructure. The
development model followed by modern economies has reduced dependence on nature
to produce such services. While a few services such as food and timber
production are maintained, many ecosystem services have been put at risk by
industrialisation. Agricultural intensification, for example, is partly
responsible for the loss of bees and other species which are essential to
pollinate crops and maintain production levels[5].
Air pollution, e.g. NH3 from the use of fertiliser and manure handling in
agriculture, can lead to acidification and eutrophication. As a result,
ecosystem services are mainly produced at present in regions where rural areas,
mountains, wetlands, forests or coastal areas are important. 
The potential capacity to produce ecosystem
services in NUTS 2 regions is illustrated by Map 71 by means of a composite
indicator, TESI - a total ecosystem services index, based on 13 individual
indicators, each measuring the capacity to provide a particular service (production
of food, livestock, water and timber; regulation of air, climate, soil quality,
water and water quality; pollination, erosion, coastal areas protection and
provision of recreational services). Four of indicators reflect provisioning
services: the goods or products we obtain from ecosystems. Eight indicators
refer to regulating services: the benefits we obtain from an ecosystem’s
control of natural processes. One indicator refers to a cultural service:
recreation, which is a non-material benefit obtained from ecosystems[6].
In general, regions with a low TESI, where a
large part of the land area is taken for producing crops and urban development
have less land left where ecosystems, such as forests and wetlands, can provide
their services. By contrast, regions with a higher TESI have a wider and more
balanced array of ecosystem services. The difference between medium and high
TESIs results from more or less productive ecosystems, For example, wetlands
and forests often generate higher levels of service than grass- or shrub-land.
As indicated above, green infrastructure
comprises all natural, semi-natural and artificial ecosystems. There is a
strong positive relationship across the EU between the area of a region covered
by green infrastructure and its capacity to provide ecosystem services (Map 72).
Investing in green infrastructure should therefore increase such services. 
Map 72 shows that even in regions where land is
predominantly used for growing crops many ecosystem services can still be
present. For instance, a recent study in the UK indicates that converting
comparatively small amounts of land from agricultural use to open-access
recreation leads to a relatively modest loss in farm produce but generates much
larger social benefits[7].
 Map 3: Capacity to deliver ecosystem services, TESI index, EU NUTS 2 regions || Map 4: Green infrastructure, EU NUTS 2 regions (% of the surface area covered with green infrastructure) 
Figure 46 Green infrastructure and the delivery of ecosystem
services
In order to identify properly the types of
action capable of increasing the benefits from the ecosystem, demand aspects
also need to be taken into account. Demand for ecosystem services tends to rise
as population density increases or human settlements are established. The
action required to increase ecosystem services therefore differs between
places, according to the specific features of the locality. This often implies
a need to consider much smaller areas than NUTS 2 regions, as illustrated by
the following examples relating to improving air and water quality.

5.4.1.   Air
quality is still too low in many EU cities

As noted above, air pollution is a major
environmental concern in cities across the EU. The removal of air pollutants
and dust from the atmosphere is an ecosystem service provided to a large extent
by forests and other wooded lands[8].
Regions in North Sweden and Finland have many such areas and so have a high
capacity for providing this service. However, given their low population
density, demand for the service in these regions is low especially compared
with urban areas. It is therefore in the latter that policy action to increase
the capacity of ecosystems to regulate air quality should be concentrated[9]. This can be done by
investing in green infrastructure such as urban parks and green spaces, so that
trees can help to reduce temperature, contribute to natural urban ventilation
(dispersion of air pollutants)  and remove pollutants such as NO2 from the
atmosphere. As just planting trees can also cause local hotspots of (other) air
pollutants (e.g. PM) if not done properly, such action, however, needs to be
part of an integrated strategy for improving air quality in EU cities.
 Map 5: Removal capacity in larger urban zones || Map 6 NO2 daily average concentrations, 2011 
Computer models which include data on air
quality as well as details of green urban areas can be used to quantify the
amount of pollutants that can be removed from the atmosphere by this means. The
economic benefits of removing air pollutants can then be calculated by
estimating the reduced costs of pollution to society not accounted for in the
market price of goods and services, like electricity and transport, responsible
for pollution. 
The capacity of cities in the EU to regulate
air quality differs greatly. This is illustrated by the example of nitrogen
dioxide (NO2), which is a major air pollutant released during the
burning of fossil fuels. Map 73 illustrates how urban green areas contribute to
NO2 removal in larger urban zones across the EU.
The removal capacity of NO2 per
inhabitant differs widely between larger urban zones, depending primarily on
the ratio between forested areas and population. Most large urban zones in
Scandinavia, in Central and Eastern Europe (with the exception of Bulgaria and Romania), in Germany have a relatively high capacity to remove NO2 per
inhabitant. The removal capacity is much less in Southern Europe (except in Portugal) but also in Northern Italy and the UK. 
In many EU cities NO2 concentrations
are high (Map 74), especially in the larger ones. For example, Milan and Madrid have high concentrations and a low removal capacity. Some cities like Berlin and Stockholm have a high removal capacity, which explains in part why their
concentrations are lower than in other large cities. But these cities can also benefit
from investment in removal capacity to further reduce concentrations, such as in
green infrastructure like suburban woods, parks or green roofs[10].

5.4.2.   Floodplains
can regulate water flows and improve quality
efficiently

Floodplains are land areas bordering seas,
lakes and rivers that are subject to recurrent flooding. If managed properly,
floodplains can produce important ecosystem services. First and foremost, they
prevent downstream areas from being flooded and so play an essential role in
reducing the risk of disasters. Floodplains and wetlands also provide other
services, in particular by purifying water, as they are very effective in
retaining, processing and removing pollutants, sediments and excess nutrients,
which avoids pollution downstream and more importantly, helps to provide clean
water. As well as acting as natural water storage reservoirs and treatment
plants, floodplains also provide a habitat for many species of flora and fauna
and so are key to preserving biodiversity. 
Water purification is another less known
ecosystem service provided by floodplains. Floodplains are particularly
efficient in combating excessive nitrogen loading from artificial fertilisers
and the combustion of fossil fuels, which affects the quality of water in many
places and is a major cause of water pollution. Excess nitrogen runs into
rivers, streams, lakes and further downstream into estuaries and coastal zones
causing eutrophication which results in excessive algae and, on occasion, in
harmful cyanobacterial harmful algal blooms (CyanoHABs).
Once a floodplain is flooded during high water,
it starts removing nitrogen. Using floodplains as temporary reservoirs at times
of peak flow can, therefore, substantially increase the capacity of rivers to
retain, process and remove nitrogen from water. As Map 75 shows, a number of
river basins in the EU such as the Rhine or Meuse, can provide such a service
to densely populated areas and cities. (The map shows the total nitrogen discharge
of major European rivers and simulates the potential retention of nitrogen
under a scenario of implementing a floodplain strategy.)
Map 7: Nitrogen discharge/retention from Europe's major rivers
Integrating floodplains as temporary reservoirs
in times of peak flow increases substantially the capacity of the river network
to retain, process and remove nitrogen from water. For instance, model
simulations show that reconnecting floodplains to rivers in areas where this is
possible is expected to reduce the total nitrogen load of river basins to
European seas by 7% on average[11].

6.     Conclusion

Cohesion policy has a major role to play in
helping EU regions to adopt more sustainable modes of development and address
the many environmental challenges they face in the future. The analysis set out
in this chapter has highlighted the wide variations in the performance of EU
regions with regards issues related to environment. 
The impact of climate change will differ
considerably from one region to another, according to its location but also to the
main economic activities situated there, the features of its human settlements
(e.g. urban as opposed to rural) and the characteristics of its population
(e.g. young or old). This implies a need to adopt adaptive measures tailored to
the local context in order to limit the devastating impact of climate change in
all, but especially the most vulnerable regions. 
EU regions can also play a major role in
limiting the extent of climate change by contributing to the targets set out in
the EU Climate and Energy Package. In particular, Cohesion Policy can help
national, regional and local public authorities to reduce GHG emissions in the
sectors not covered by the emissions trading scheme such as transport and
buildings. It can also support the expansion of renewable energy supply and
contribute to increase energy efficiency, notably in public buildings and
public transport.
Many of such measures aiming for transport,
energy efficiency and renewable energy fit also well in Air Quality Plans under
Directive 2008/50/EC to reduce concentrations of Particulate Matter, NO2
and ozone, leading to better health for citizens and less damage to crops,
buildings and ecosystems.
Although the situation has improved over
time, substantial efforts remain to be made to enhance the treatment of urban
wastewater in many EU regions, both in the EU12 and the EU15. The same holds
for waste management. Considerable progress has been made to increase recycling
and energy recovery and to reduce landfill, but some regions still need major
investment to increase their capacity to treat waste in a way which is less
damaging to the environment.
In addition, Cohesion Policy can help EU
regions to increase the quality of their environment. This is not only
necessary to improve well-being in general but it can also lead to substantial
benefits as sound ecosystems generally have positive effect on health and offer
vital services such as clean drinking water, breathable air, carbon
sequestration or regulation of water flows. Cohesion policy can help to improve
air quality in the urban centres where it is needed and to restore the capacity
of ecosystems to deliver their services where these have deteriorated. In this
perspective, supporting investment in green infrastructure is particularly
appealing since it is often an effective and cost-efficient solution while at
the same time it contributes to achieving the objectives which the EU has set
for limiting biodiversity loss.
[1]       See also Commission Report (COM(2013)574final ‘7th
report on the Implementation of the Urban Waste Water Treatment Directive
(91/271/EEC) – figures exclude Croatia.
[2] Data on mineral waste are still of low data quality and have
therefore been omitted from the calculation.
[3]       An ecosystem is a dynamic complex of plant, animal,
microorganism communities which interact with the non-living environment as a
functional unit. Humans are an integral part of ecosystems.
[4]       Green infrastructure cn be defined as natural land areas, working landscapes and other open
spaces enhancing the capacity of
ecosystems to provide goods and services.
[5]       Zulian G., Maes J., and Paracchini
MP.,2013, Linking land cover data and crop yields for mapping and assessment
of pollination services in Europe, Land 2, 472-492.
[6]     Details concerning the methodology are described in Maes J, Paracchini ML, and Zulian G.,
2011, A European assessment of the provision of ecosystem services, Towards
an atlas of ecosystem services. EUR 24750 EN, Publications Office of the European Union, Luxembourg and Maes J., Paracchini
ML., Zulian G., and Alkemade R., 2012, Synergies and trade-offs between
ecosystem service supply, biodiversity, and habitat conservation status in Europe, Biological Conservation 155, 1-12.
. Note that the TESI indicator has
not been agreed in the context of the Mapping of Ecosystem Services (MAES).
[7]       Bateman IJ., et al., 2013, Bringing
Ecosystem Services into Economic Decision-Making: Land Use in the United Kingdom, Science 341(6141), 45-50.
[8]       The difference between forests and
other wooded lands is the extent of canopy coverage. Although there is no
general EU definition for these land categories, the FAO definition of
"forest" requires a minimum of 30% tree canopy cover, whilst other
wooded land" has a canopy cover between 10 and 30%.
[9]       Forests, even in sparsely populated areas, obviously remain
key natural assets to provide services such as climate regulation, CO2
absorption, regulation of the hydrologic cycle and habitats for migratory
birds.
[10]     A green roof is one that is partially or completely covered
with vegetation. Its serves several purposes such as absorbing rainwater,
providing insulation, creating a habitat for wildlife, and helping to lower
urban air temperatures so mitigating the heat island effect.
[11]     Maes J. et al., 2012, A spatial assessment of ecosystem
services in Europe: methods, case studies and policy analysis - Phase 2,
Synthesis, PEER report no 4, Ispra, Partnership for European Environmental
Research.
Chapter 4: Public
investment, growth and the crisis

1.     Introduction

The financial and economic crisis which
started in 2008 had a dramatic impact on public finance all over Europe. Contraction of economic activity reduced the tax base and hence public revenue at a
moment where expenditure was rising as a result of the counter-cyclical
measures put in place in the Member States, the rise in unemployment and the
support given to the banking system. 
This has led to a significant increase in
public deficit and public debt in most Member States which triggered a
counterbalancing move of the fiscal stance towards consolidation, starting in
early 2010. This translated into a reduction in public expenditure in a number
of European countries. Growth enhancing public expenditure in areas such as
education, R&D, ICT and transport infrastructure has been particularly
affected compared to other items of public expenditure.
This has substantial implications for
Cohesion Policy, which provides support for national, regional and local
authority investment in growth enhancing area. Policy measures financed by
Cohesion Policy have to be complementary with those initiated by Member States.
Their effectiveness is put at risk if the resources allocated by the Member
States to this type of expenditure are not sufficient. 
Secondly, in a context where Member States
reduce growth-enhancing expenditure, the role of Cohesion Policy becomes
critical for financing public investment, which is important for maintaining
growth potential and so for creating the conditions for successful and
sustainable fiscal consolidation and reduction in debt in the future. The
stance of fiscal policy and public finance developments at various levels of
government in the Member States are therefore major elements of the context in
which Cohesion Policy is operating that determine its capacity to deliver
results.

2.     the
share of growth enhancing spending in public expenditure has decreased
2.1.      The
crisis pushed up government deficits

Public finances in the EU significantly
worsened after the onset of the financial and economic crisis that started in
September 2008 (Figure 1). From
2000 to 2008, the public sector balance in the EU-27[1] fluctuated around an
average deficit of 1.9% of GDP, with a surplus of 0.6% of GDP in 2000 and a
maximum deficit of 3.2% in 2003. Starting in 2008, the average deficit began to
increase sharply, reaching 6.9% of GDP in 2009. In 2010, the deficit stabilised
at 6.5% of GDP and was then progressively reduced to 4.4% of GDP in 2011, 3.9%
in 2012 and 3.3% in 2013, largely because of the fiscal consolidation measures
implemented from 2010 on.
Figure 1 – General government balance, EU-27
average, 
2000-2013 (% of GDP)
 Average 2009-2013 
 Average 2000-2008 
Source: Eurostat
The same broad pattern is evident in most
Member States, though there are considerable variations between them in the
scale of the changes. The deterioration in public finance was much more severe
in some Member States than in others (Figure 48). In Spain and Ireland, a surplus of 2-3% of GDP in 2006 was transformed into a deficit in 2009 of around 11% in Spain and 14% in Ireland. There was also a dramatic increase in the deficit in Greece, from 5.7% of GDP in 2006 to 15.6% in 2009, as well as in Latvia, from 0.5% of GDP to 9.8%
over the same period. In Luxemburg and Sweden, there was only a small change in
the balance and in Hungary, where there were serious budgetary problems before
the crisis struck, the deficit was reduced by fiscal consolidation measures from
9.4% of GDP in 2006 to 4.6% in 2009. 
Figure 2 – General government balance, Member
States 
(ordered by deficit in 2012), 2006, 2009 and 2013 (as % of GDP)
 Source: Eurostat
In 2013, the deficit was largest in Slovenia (14.7% of GDP)  and Greece (12.7%), followed by Spain (-7.1%) and Ireland (7%), while Luxembourg was in surplus (0.1%) and Germany on balance (0%). The deficit was
lower than 1% in Denmark, Latvia and Estonia. The dramatic increase of the public
deficit in 2009 was due to a large extent to the sharp decline in Government
revenue that followed the reduction in economic activity resulting from the
financial crisis and global recession (Figure 3). Government revenue in the
EU-27 in real terms fell on average by 5.3% in 2009. It then increased in the
three subsequent years (by 1.9% in 2010, 2.9% in 2011 and 1.4% in 2012), mostly
because of the slight improvement in the economy (which expanded the tax base) together
with increases in tax rates as well as measures to improve the collection of
taxes in a number of Member States. 
Government expenditure in the EU increased steadily
in real terms during the years preceding the crisis, rising on average by 2.4%
per year between 2000 and 2008. It then increased by 3.6% in 2009 and 1.2% in
2010 before declining by 1.5% in 2011 and then overall stabilising in 2012 and
2013 with nevertheless a slight downward trend. The expansion in 2009 reflects
the combined effect of the automatic stabilisers which led to an increase in
social transfers resulting from rising unemployment and the policy decisions
providing substantial support to banks in difficulties as well as the fiscal
stimulus packages put in place at the end of 2008. The subsequent movements
reflect the fiscal consolidation programmes, which started to be implemented in
2010. 
Figure 3 – General government expenditure, revenue (EUR bn, 2005 prices) 
and general government balance, EU-27, 2000-2013 (% of EU GDP)
Source: Eurostat
The same broad pattern of change applies to the
majority of Member States, although there were significant variations between countries
in the scale of movements (as highlighted in Figure 4). After growing at a
moderate rate up to the onset of the crisis in most countries, government expenditure
declined in real terms in 15 countries between 2009 and 2013. The decline was
particularly pronounced in Greece, Lithuania, Romania and Ireland (where expenditures respectively fell on average by 3.8%, 3.0%, 2.7% and 2.6% a year
between 2009 and 2013). In other Member States, public expenditure also
declined though at a slower pace, below 2%, reflecting the EU-wide policy of
fiscal consolidation. Public expenditure was on an upward trend since 2009 in
13 Member States, in general those where the impact of the crisis was less
dramatic.
Figure 4 – Average annual change in general government expenditure, 
volume, 2000-2009, 2009-2013 (%)
Source: Eurostat. Average 2002-2009 for Croatia.

2.2.      Public investment supports
economic growth 

It is commonly accepted in the economic
literature that government expenditure may have an impact on economic activity
in the short run and growth in the longer run, though there is no precise
relationship between the former and the latter because it depends on a large
number of factors. There is an overall consensus, however, that efficient regulation,
an effective and a well-functioning public administration, and well-targeted
and tailored public expenditure all are essential to the smooth functioning of
modern economies by providing essential infrastructure and public services,
ensuring the rule of law and enforcing property rights.
Such services include education and support for
R&D both of which are important for long-term growth. Both, however, are
likely to experience under-expenditure without government intervention since
individuals when making their spending decisions will not tend to take account
of the wider benefits to society and the economy which such expenditure gives
rise to. 
Recent research suggests that government
expenditure can act as an important stimulus to the economy during a period of
recession when the private sector is reluctant to invest and when its impact on
economic activity is, accordingly, likely to be greater, It also suggests that
it can have significant cross-border effects at such a time, leading to growth
being spread through trade linkages across the EU economy, just as the depressing
effects of fiscal consolidation can equally be spread from one Member State to
others (see Box for a summary of the economic literature on these various
effects of government effects).

Box: The
economic literature on the effect of government expenditure on growth

There is wide agreement on the essential role of governments in
investing in infrastructure and on the positive effect of this on economic
growth (see e.g. Gramlich (1994)[2]). There is equally broad agreement that government
intervention is needed to correct the tendency for the private sector to
under-invest in education and R&D, because of a failure to take account of
the social as well as the private returns. While there is a vast literature
linking public support to education with growth, the fact that the links tend
to be very long-term makes it difficult to identify them in the data.
Nevertheless, the evidence points to a positive impact that expenditure on
education has for growth (see Blankenau et al. (2007[3]). 
Whereas the positive effect of R&D on productivity growth is beyond
doubt (see Griliches (1994[4])), it is more difficult to assess the effect of
public support for R&D. This is, first, because of a need to allow for
possible ‘deadweight’ effects arising from the fact that the expenditure on
R&D might have taken place even without government support (see, for
example, Bronzini and Lachini, 2011[5], who find that subsidies do not alter the
behaviour of large firms). Secondly, even if a positive effect is observed, it
is difficult to determine whether the resulting increase is compensating for
underinvestment as predicted by theory or for other market failures such as
difficulties of SMEs accessing finance for R&D. This is still an open
question on which there is intensive research.
The impact of public expenditure on economic activity in the short term
involves estimating the ‘fiscal multiplier’, as first formalised by Richard
Kahn (a student of J.M. Keynes) in 1931, which is defined as the change in
output resulting from a given change in government expenditure, taxes or a
combination of both. The recent global recession has sparked renewed interest
in estimating the size of this multiplier.
Estimates of the multiplier vary over time and between economies and
depend on the type of model applied and the assumptions made. In broad terms,
the size of the multiplier seems to be affected by factors such as the presence
of financial friction, the credibility of the policy action concerned and its
permanent or temporary nature, its composition, the presence or absence of
market rigidities, the size of automatic stabilisers, the type of monetary
policy in force, the degree of openness of the economy and the exchange rate
regime (European Commission (2012[6])). 
The many estimates of the fiscal multiplier vary markedly in terms of
size. Some estimates put it at less than one (see e.g. Barro (1981), Perotti
(2005) and Barro and Redlick (2011))[7], others at greater than one (Blanchard and Perotti (2002),
Beetsma and Giuliodori (2011) and Ramey (2011)) and even as high as 1.6% (Beetsma, Giuliodori and Klaassen (2008)[8]). Some analysis even point
to negative multipliers (see e.g. Giavazzi, Jappelli and Pagano (2000)[9], Giudice, Turrini and in’t
Veld (2007)[10] or Di Comite et al. (2012)[11]) 
On the theoretical front, until recently most models were unable to
produce multipliers significantly larger than one (see e.g. Aiyagari, Christiano and Eichenbaum (1992),
Baxter and King (1993), Ramey and Shapiro (1998) and Cogan et al. (2010[12])) due to the neo-classical features incorporated in them. Specifically,
an expansionary fiscal policy is offset by consumers being assumed to take
account of the future taxes they will need to pay to service increased public
borrowing and so limiting any increase in their spending. Equally, increased
borrowing to finance additional government expenditure is assumed to push up
interest rates, so reducing – or ‘crowding out’ – private investment. The
multiplier is, therefore, reduced as a consequence.
More recent models, however, suggest that the multiplier in periods of
economic downturn may be higher than during periods of growth (as high as 2.5
as against 0.6, according to Auerbach and Gorodnichenko, 2013[13]). This asymmetry arises from certain
features of recessions which are embedded in the new models – in particular,
households being unable to borrow (Krugman and Eggertsson, 2012[14]), downward rigidity of nominal wages and
financial friction (or the costs involved in making a transaction) – which tend
to increase the multiplier in downturns as compared with periods of expansion.
In addition, particular focus has been put by some authors on the
difficulty of reducing interest rates below zero so making monetary policy
ineffective. Recent estimates of new-Keynesian models incorporating this
feature are that the multiplier in such periods is between 3 and 5 because
private investment and consumption are not crowded out by public spending
(Christiano, Eichenbaum and Rebelo, 2011, Egertsson, 2009, Woodford, 2011[15]). Accordingly, an increase in government expenditure
can have a major effect on economic activity when monetary policy can do
little. 
Recent research in the European Commission (In 't Veld (2013[16])), moreover, highlights the importance of
cross-border spill-over effects through trade linkages from fiscal
consolidation which reinforce the negative impact on output. 
The greater than expected impact of public expenditure on output during
recessions has been corroborated by recent empirical studies (e.g. Corsetti,
Meier and Müller (2012), Auerbach and Gorodnichenko (2012a), Baum,
Poplaski-Ribeiro and Weber (2012)[17]). These conclude that earlier research may
well have underestimated the effects of fiscal policy on output in recessions
and overestimated it in expansions (Auerbach and Gorodnichenko, 2012b And
Blanchard and Leigh, 2013). 
This would imply not only that am expansionary fiscal policy was more
effective in stimulating growth during a recession than previously thought, but
also that fiscal consolidation during such times entails bigger downward pressure
on economic activity. At the same time, the effects of consolidation on growth
need to be weighed against the importance of restoring sound public finances.
As demonstrated by experience, Member States which have accumulated large
amounts of debt can be subject to sudden reversals of market sentiment which
could turn into outright financial crises if sizeable corrective measures are
not taken. 

2.3.      Public expenditure increased, but now come down

As highlighted above, some categories of public
expenditures are considered to be growth-friendly, in the sense that they can
increase the rate of growth in the future. This is the case as regards expenditure
on, for example, education, health care, environmental protection, transport,
R&D and energy.[18]
The deterioration in public finances and the
fiscal consolidation measures which began to be implemented at the end of 2010
have resulted in significant changes in the composition of public expenditure
in a number of Member States. In particular, growth-friendly expenditure has been
cut back disproportionately as part of fiscal consolidation measures[19].
Growth-friendly expenditure as a share of the
total decreased in the EU-27[20]
as a whole between 2008 and 2012, from 36.7% to 35.6% (Figure 5).
The drop was particularly severe in Portugal (-8.1 percentage points), Slovakia (-7.9), Ireland (-7.4) and Greece (-7.2) The share increased in only 7 Member States,
generally those which were less affected by the crisis and where fiscal
consolidation was limited.
Figure 5 –
General government expenditure on growth friendly categories
(% of total general government expenditure), 2012.
Source: Eurostat. 

2.4.      Public
investment increased and then dropped

The crisis has had a major effect in reducing private
sector investment (Figure 6). Public
investment (here defined as gross fixed capital formation of General
Government), which had remained fairly stable for a decade, increased
significantly between 2007 and 2009, performing a counter-cyclical role by
compensating, at least in part, for the decline in private investment. Since
2010, however, public investment has fallen while private investment has continued
to decline due to sluggish growth prospects. According to the latest Commission
forecasts for 2013 and 2014, investment in the EU-27 will reach historically
low levels for General Government (in 2014) having done so in respect of the
private sector in 2013. 
Figure 6 - Public and private fixed investment, EU-27, 1995-2014 
(Gross Fixed Capital Formation as % of GDP)
Source: Eurostat 

3.     Regional
and local authorities play a key role in public expenditure and investment
3.1.      Regional
and local authorities are responsible for a large share of public expenditure 

The share of sub-national expenditure in total general
government spending has increased in most EU countries over the past few decades
as the role of regional and local authorities in delivering public policies has
increased. Nevertheless, the share varies considerably between countries, largely
reflecting differences in the institutional setting and the degree of
decentralisation. Sub-national levels of government tend to be most important in
Federal States, like Austria, Belgium and Germany or in countries like Spain and Sweden where there is high degree of de-centralisation. It is important to note, however,
that responsibility for undertaking expenditure is not necessarily synonymous
with decision-making powers (European Commission, 2012; Governatori and Yim,
2012[21]).
Regions and local authorities are responsible
for around 66% of total public expenditure in Denmark and for almost 50% in Sweden and in Spain. In Greece, Cyprus and Malta, they are responsible for less than 6% (Figure 52).
Overall in the EU-27[22],
the share of sub-national authorities increased by 2 percentage points between
1995 and 2013, with much bigger increases in Spain, Romania, Denmark and
Sweden, and significant reductions in Ireland and the Netherlands.
Figure 7 -
Sub-national governments expenditure in general government expenditure, EU-27,
1995 and 2013 (% of general government expenditure)
Source: Eurostat.
In relation to GDP, sub-national government
spending averaged 16% in the EU-28 in 2013, ranging from less than 1% in Malta
to almost 38% in Denmark (Figure 8).
Figure 8 -
Sub-national government expenditure, 2013 (% of GDP)
Source: Eurostat
Types of expenditure carried out by
sub-national levels.
The expenditure of sub-national authorities is
concentrated in particular areas, most especially in education, social services
and housing, but also in healthcare, transport and communications[23] (Table 1). There are, however, large variations
between Member States, reflecting the degree of decentralisation, the
peculiarities of federal systems and the particular responsibilities entrusted
to sub-national authorities.
In some countries, Denmark in particular, a
large share of sub-national expenditure goes on social services, while in
others, this is much less the case, such as in Italy, where the share is only
5% and where instead much more goes on healthcare. 
Table 1 -
Sub-national governments expenditure by function, 2013 
(% of total Sub-national governments expenditure)
Source: Eurostat. Expenditure of local and state levels are not consolidated.
The overall expenditure of sub-national
authorities is higher than that of central governments on many public services,
such as education, cultural activities, water supply, public lighting and other
community amenities and environmental protection (Table 2). In some
Member States, public expenditure in these areas is almost entirely carried out
by sub-national levels of government, though in many cases financed nationally through
transfers from central government, which are often earmarked for these services[24].
This, for example, is the case for housing in Belgium, Estonia, Latvia, Lithuania and Spain and environmental protection in Spain, Greece and Cyprus. Expenditure at the subnational level on education is particularly high in Spain and Germany, on healthcare in Denmark, Spain, Sweden, Italy and Finland, and on economic
affairs in Spain, Germany, Belgium and Italy. Apart from Denmark, social protection, however, remains largely centralised in Member States. 
Table 2 - Sub-national
governments expenditure by economic sector, 2013
(% of total general government expenditure)
Source: Eurostat. Expenditure of local and state levels are not consolidated.
Sub-national levels of government are
responsible for a large share of growth-enhancing expenditure, as defined above
(on education, healthcare, environmental protection, transport, R&D and
energy). Overall, in 2011, they carried out over 46% of such expenditure in the
EU-27, this accounting for 38% of their total spending.
The sub-national responsibility for the
expenditure concerned, however, varies markedly between countries (Figure 9). On
average, sub-national government spending amounted to around 8% of GDP in the
EU-27 in 2012 but as much as 14% of GDP in Sweden and Denmark and as little as 0.3%
in Cyprus and Malta. In eight Member States, sub-national governments were responsible
for more than 50% of the growth-enhancing expenditure of General Government,
the figures being highest in Sweden, Italy, Spain, Denmark and Finland. 
Figure 9 -
Growth Enhancing Expenditure, 2012 (% of national GDP)
Source: Eurostat

3.2. Regional and local authorities manage the majority of public
investments

Sub-national governments contribute
significantly to public investment[25].
In 2013, around 55% of total public investment in the EU-28 was carried out by
sub-national authorities (Figure 10). The share was particularly large
in Germany, Belgium, Finland and France (over 65%). There are only a few Member
States – Greece, Cyprus and Malta, especially – where sub-national governments account
for only a minor share of public investment. These are generally countries
where sub-national authorities are responsible for a very small share of total
public expenditure. 
Nevertheless, the share of sub-national
authorities in public investment has declined since 2000 in 14 Member States,
most especially in Ireland where it fell from 60% to 21% in 2013. As shown in
the next section, this is to a large extent a consequence of fiscal
consolidation measures implemented in response to the financial and economic
crisis.
Figure 10 -
Sub-national governments investment, 2000 and 2013
(% of total public investment)
Source: Eurostat

3.3.      The crisis ended a period of sustained growth of public
expenditure by regional and local authorities

From 2000 up until 2009, public expenditure at
the subnational level in the EU fluctuated around an average of just under 16%
of GDP. In real terms, it grew at an average rate of 2.8% a year. In 2009, it
increased by 3.4%, partly as a result of the fiscal stimulus package as well as
the additional demands on social services. Fiscal consolidation measures implemented
from 2010 on brought growth to an end, expenditure remaining unchanged in 2010
and then declining by 0.5% in 2011, 0.8% in 2012 and 2.2% in 2013.
A similar pattern of change is evident in most Member
States. Except in Malta and Germany, growth in public expenditure at
sub-national levels has been cut back in all countries (Figure 11), in
a number of them – such as Hungary and Ireland, where it declined by 11% a year
and 9% a year between 2010 and 2013 – substantially so. 
Figure 11 -
Average annual change in sub-national government 
expenditure, volume, 2000-2009, 2010-2013 (%)
Source: Eurostat, Average 2002-2009 for Croatia.
The capacity of sub-national authorities to
contribute to public investment in particular has been significantly affected
by the fiscal consolidation packages implemented across the EU. Public
investment at sub-national levels in the EU-27[26]
increased steadily from the mid-1990s on to stabilise at around 2.3% of GDP between
2002 and 2007 (Figure 12). It
then rose to 2.5% in 2009, partly as a result of stimulus measures. From 2010, when
fiscal consolidation measures began to be introduced, to 2013, it declined
sharply to 1.8% of GDP, much lower than the level observed in 1997. In real
terms, sub-national public investment in the EU fell by 7.2% in 2010, 5.9% in
2011, 3.3% in 2012 and 8.6% in 2013. 
Figure 12 -
Sub-national government investment, EU-27, 1997-2013 (% of GDP)
Source: Eurostat.
Between 2009 and 2013, public investment at
the sub-national level declined in real terms in 20 Member States. In most of
the others, it continued to grow though at a slower pace. Growth was higher
than before the crisis only in Belgium, Finland, Estonia, Sweden and Malta (Figure 13). The turnaround was most
striking in Spain, where sub-national public investment increased by more than
4% a year in real terms between 2000 and 2009 and then declined by more than 22%
a year between 2009 and 2013. It also fell significantly in Ireland (by 18% a year), Cyprus, (16%), Slovakia (13%) and Portugal (12%). 
Figure 13 –
Average annual change in sub-national government investment, volume, 2000-2009,
2010-2013 (%)
Source: Eurostat. Average 2002-2009 for Croatia.
These reductions imply that in 2013 public
investment was lower relative to GDP than at any time since 1997 in seven
countries of the EU-27, most notably in Spain (where it fell from 4.3% of GDP
in 2009 to 1.5% in 2013) and Ireland (where it declined from 3.5% of GDP in
2008 to 0.9% in 2013).
Figure 14 - Sub-national governments' investment,
1997, 2013 and historical lows
(% of national GDP)
Source: Eurostat. Data not available for
  Croatia in 1997.

3.4.    Investing during times of crisis: direct financing and
regional and local investment

As indicated above, sub-national public
investment has been severely affected by the crisis and the fiscal
consolidation measures implemented in response to it. A study carried out by
OECD (with a contribution from the European Commission) found that the OECD countries
that faced the most serious economic difficulties over the period 2007-2011 saw
the largest reductions in sub-national investment. A new indicator of direct-financing
capacity, designed to measure the funds available to sub-national governments to
finance investment without going into debt, shows that their capacity declined
significantly over this period. As shown by Figure 61, capacity is closely
correlated with spending on investment, which indicates that sub-national
governments that generate the fiscal capacity to spend on investment tend to do
so.
Figure 15: Sub-national direct financing capacity and public
investment
Source: OECD.
Analysis of recent trends in sub-national
finances shows that these were reduced significantly by the crisis. Expenditure
on social services and transfers to companies, however, were maintained and
even increased in some cases, so reducing the ‘fiscal space’ left for public
investment.
Sub-national authorities were also faced by a
worsening of borrowing conditions. The introduction of rules governing their
borrowing or a tightening of those already in place which occurred in many OECD
countries as part of fiscal consolidation measures further reduced their
capacity to invest.
The OECD has highlighted the likelihood that
this capacity will continue to be restricted over the medium-to-long term. In
such a context, the institutional setting is likely to play an important role
as regards both revenue (the income likely to be generated by local taxes) and
expenditure (their spending responsibilities). In most OECD countries,
demographic trends are likely to generate fiscal pressure on sub-national
governments responsible for spending on healthcare and social services. 
Central governments are well aware of future
challenges likely to be faced by sub-national authorities and have introduced
measures to control their revenue and debt levels in a number of countries. In several
countries too, governments are seeking to gain economies of scale in public
service provision by merging local authorities or establishing more co-operation
between them. However, in countries where sub-national governments have major responsibility
for expenditures in areas where pressure is likely to increase, further efforts
will be needed to maintain their ability to provide high-quality services in
the medium-to-long term. 

3.5.      Revenue at sub-national level
relies primarily on transfers

Revenue of sub-national governments in the EU
has been significantly affected by the crisis. While their revenue increased relatively
consistently at a rate of around 2.5% a year in real terms on average between
2000 and 2009, it decreased by 0.1% a year between 2009 and 2013.
Over these four years, sub-national government revenue
declined in 12 Member States (Figure 16). The fall was particularly large in
 Ireland, Cyprus, Hungary and Spain. In the other countries, revenue continued
to grow but at a much slower pace than before the crisis. The only exceptions
are Austria, Germany, Sweden and Malta where the growth of revenue was higher after
2009 than before. 
Figure 16 – Annual
average change in sub-national government revenue in real terms, 2000-2009,
2009-2013 (%)
Source: Eurostat. Average 2002-2009 for Croatia.
The causes of these changes in sub-national
government revenue differ between countries, depending on the sources of
revenue. The main sources across the EU are current and capital transfers from
central government. This is especially the case in Malta, Romania, Bulgaria and the Netherlands. In Germany, Austria, Spain and Sweden, in contrast, it is local
taxes, reflecting the much greater degree of autonomy of sub-national
authorities in the latter than the former. Transfers also provide a means of
maintaining central government control over local expenditure. 
Figure 17 - Sources of sub-national government
revenue, 2013 (% of total revenue)
Source: Eurostat
In some cases, the decline in revenue after
2008 mostly stems from a reduction in income from local taxes, as for instance
in the UK.[27]
But in many Member States, it is due to a cut in transfers from central
government. However, transfers go in both directions, since revenue from local
taxes or sales by local authorities (such as of housing) can be transferred to central
government. In some Member States, these transfers are significant and need to
be taken into account when assessing changes in sub-national government income.
In most of the Member States which were hit hard by the global recession, net
transfers from the central government to local authorities were reduced significantly
between 2009 and 2012. This was particularly the case in Spain in respect of
net transfers to regional authorities which were reduced by 96% in real terms,
as a result of both transfers from central government being reduced markedly
(by 42%) and transfers from the regions to the centre being increased
substantially (from only just around EUR 1.4 billion to EUR 32.2 billion at
2005 prices). A similar trend, but with less of a reduction, was also
registered by Spanish local authorities. There was equally a significant
reduction in Ireland, Czech Republic, Latvia and Italy. By contrast, central
governments provided increased support to local and regional authorities in 14
countries, especially in Germany (both for Länder and local authorities), Lithuania, Sweden and Luxembourg. It is no coincidence that in most of the countries in which net
transfers to sub-national authorities increased, the recession was of limited
duration and there was less need for fiscal consolidation.
Figure 18 –
Change in net transfers between central and State-local Governments, 
2009-2013 in real terms, 
Source: DG
REGIO calculations based on Eurostat data. Note: in line with the Eurostat
public accounts dataset financial transfers for Germany, Austria, Spain and Belgium are calculated for two different levels of sub-national governments
(S1312 state government, corresponding to federal/regional authorities and
S1313 local government, corresponding to local authorities).

3.6.      Public
deficit and public debt of sub-national governments

As for all parts of the public sector in the
EU, public finance at the sub-national level deteriorated significantly following
the onset of the financial and economic crisis[28].
While a small deficit of 0.1% of GDP was observed in 2007, public finance at
sub-national level was in deficit to the tune of 0.8% of GDP in 2009 and 2010. This
deterioration was mainly due to a fall in revenue in 2008 and 2009 (Figure 18),
stemming mainly from the reduction of transfers from the central government. Fiscal
consolidation measures then began to have an effect and the deficit was
progressively reduced to 0.1% of GDP by 2013 returning to its 2007 level.
Figure 19 – Sub-national government expenditure,
revenue (EUR bn, 2005 prices) and sub-national governments deficit (% of EU
GDP), EU-27, 2000-2013
Source: Eurostat
The deterioration of sub-national public
finance is more significant in some Member States, particularly in Belgium, Spain, Finland and Germany where the deficit increased by more than 0.5 percentage points
between 2007 and 2013. In a few others, on the other hand, public finance at
sub-national level improved, as in Hungary, Bulgaria, Portugal and Greece. 
In 2013, the deficit at subnational level was largest
in Spain and Finland (1% of GDP), while at the other extreme there was a
surplus in Hungary (2.6% of GDP) and Greece, Czech Republic and Bulgaria (0.4% of GDP).
Figure 20 - Sub-national governments deficit, Member
States, 2007 and 2013 (% of national GDP)
Source: Eurostat
The result of the increase in government
deficits over the crisis period, at national as well as sub-national level, has
been to raise accumulated public debt levels dramatically, which in overall
terms rose by as much as 30 percentage points of GDP (from around 58% of GDP to
over 87%) over the period 2007-2013. The increase occurred mainly during the
recession years of 2008-2010, and the fiscal consolidation measures implemented
since then in most Member States have reduced the pace of increase. The rise
has been most pronounced in the Member States suffering the biggest contraction
in economic activity, most of which have been subject to a macroeconomic
adjustment programme – by close to 100 percentage points of GDP between 2007
and 2013 in Ireland, over 60 percentage points in Portugal and Greece and over
50 percentage points in Spain and Cyprus. 
Despite regional and local authorities being
responsible for around 30% of total General Government expenditure and about
60% of General Government investment, the increase in public debt, as in the
deficit, principally stems from central government activities. The overall
indebtedness of local authorities and regions without major legislative powers
in the EU is below 10% of GDP in all Member States. While debt at sub-national
level has increased significantly in some countries, such as Poland, Slovenia, Bulgaria and Latvia, it has been from a very low level in relation to GDP, so
limiting the rise in absolute terms. In some countries (such as Hungary as indicated above), local authorities have even been able to reduce their
indebtedness over the crisis period. 
Figure 21 - Consolidated General Government gross
debt, 2013 (% GDP)
Source: Eurostat
The deterioration in public finances has,
however, hit some regional governments hard. In particular, the debt of Spanish
regions in 2013 was over 20% of GDP and almost four times larger in 2013 than
before the crisis. This is of concern because of the critical importance of
regions in Spain for growth-enhancing expenditure and the provision of health
and education. In addition, in Belgium, the debt of the three regions has
almost doubled over the crisis period though it remains relatively low. On the other
hand, the debt of regional governments in the two other federally-organised Member States, Germany and Austria, which have been less affected by the crisis, has
declined since 2010.
Nevertheless, in Germany, sub-national public
debt amounts to around 30% of GDP and accounts for over a third of the total
debt of the public sector, the only country apart from Spain, where debt at this level represents more than 20% of the total. In both cases, sub-national
debt is held predominantly by regional authorities (the Landër in Germany and Comunidades Autónomas in Spain), the debt of local government remaining relatively
small. The latter is equally the case in other Member States, especially in the
more centralised ones.

4.     Contribution of cohesion policy to public investment in the
Member States

As shown above, public investment has declined
significantly since 2009. As a consequence, the importance of Cohesion Policy
for the financing of public investment programmes has increased further in the crisis
years. For many Member States, especially those facing a reduction in revenue
and increase of social spending, Cohesion Policy has become the main source of financing
for public investment. 
During the 2007-2013 period, the allocation
of Structural Funds and Cohesion Fund and the related national co-financing amounted
on average to around 0.55% of the EU-27 GDP each year. Despite the amount being
relatively small in relation to national public accounts indicators, the
macroeconomic implications of the ERDF, the ESF and the Cohesion Fund are
significant, especially when compared to public investment. From 2010 to 2013, these
funds represented the equivalent of around 14% of expenditure on public capital
investment in the EU and to around 21.5% of total fixed public investment[29]. 
Figure 22- Contribution of Cohesion Policy (CP) to
public investment in the EU-28 (2007-2013)
Source: Eurostat and DG REGIO
The ratio of funding to total public
investment varies substantially across Member States, which mostly reflects the
differences in aid intensity between regions and the scale of public investment
in each Member State. The highest ratios are in Member States which are recipients of
the Cohesion Fund and the ERDF under the Convergence Objective. In Slovakia, Hungary, Bulgaria and Lithuania, funding amounted to more than 75% of public investment. The
lowest ratios are in Luxembourg, Denmark and the Netherlands, countries with no
Convergence regions. Figure 64- Ratio of ERDF, ESF and Cohesion Fund
allocations plus national co-financing to total public investment (average %,
2011‑2013)
Source: Eurostat and DG REGIO
The role of
Cohesion Policy in supporting the capacity of Member States to carry out growth-enhancing
investment implies that it has a direct link to macroeconomic policy issues. Cohesion
Policy, accordingly, affects budgetary issues in the Member States not only because
it provides additional resources to finance public expenditure but also because
Member States have to co-finance EU programmes and respect the principle of
additionality[30]. The current financial and economic crisis has highlighted the need
to reinforce coherence between Cohesion policy and the renewed EU economic
governance system. This has led to the adoption of a series of reforms (described
in Chapter 6 below) intended to reinforce the linkages between the two.

5.     Investment,
state Aids, and EIB Loans
5.1.      Competition
policy

Competition policy is intended to ensure that
firms have an equal opportunity to compete wherever they are located and from
whichever Member State they originate. As government intervention is necessary
in some cases, however, the Treaty provides for situations where State aid is
considered compatible with competition in the internal market. A number of
exemptions to the general prohibition on aid are, therefore, specified.
Accordingly, State aid can be used, for example, to provide risk capital and
funding to contribute to the pursuit of the Europe 2020 objectives by
encouraging the adoption of more innovative and greener technology.
In 2011, State aid amounted to EUR 64.3
billion, or EUR 128 per head of population. In the three years 2009-2011, it
averaged 0.6% of EU GDP per year, as the measures to combat the crisis pushed
it up from 0.4% in the period 2006-2008.
State aid differs between Member States,
varying in the 2009-2011 period from 2.2% of GDP per head in Malta to just 0.1% of GDP per head in Bulgaria.
Regional aid
The Commission Guidelines on national regional
aid for 2007-2013 set out the principles for determining whether or not aid for
the economic development of disadvantaged areas, and specifically support of
investment in new enterprise creation which it entails, is compatible with the
internal market rules. This, therefore, allows higher intensity of aid in
regions with lower GDP per head and in the outermost regions. For the 2014-2020
period, the Commission has adopted new Guidelines on national regional aid,
which are part of a broader strategy to modernise methods of state aid control.
These are aimed at fostering growth in the Single Market by encouraging more
effective aid measures and at focusing Commission enforcement on cases with the
biggest impact on competition.
The new Guidelines 2014-2020 are to:
·   increase the overall share of regions where regional aid can be
granted from the current level of 46.1% to 47.2 % of the EU population, mainly
as a response to the crisis;
·   reduce the aid measures subject to Commission scrutiny as more aid
categories will be exempted from the obligation to notify the Commission
beforehand, allowing Member States to spend small aid amounts with limited
administrative burden; 
·   subject large aid measures to in-depth assessment of their incentive
effect, proportionality, contribution to regional development and effects on
competition; 
·   adopt a stricter approach to aid for investment by large enterprises
in the more developed assisted areas; 
·   in outermost regions and sparsely populated areas, maintain and
simplify the possibility for Member States to grant operating aid to companies;
·   leave unchanged the maximum 'aid intensities' for the least
developed regions. For other assisted regions, intensities are reduced
slightly, by 5 percentage points, given the reduction in EU regional economic
disparities and the need to avoid subsidy races between Member States in times
of tight budgetary constraints;
·   strengthen the anti-relocation provisions by not allowing regional
aid to the same or a similar activity to be relocated within the European
Economic Area (EEA).
Aid in
disadvantaged regions
The Treaty on the Functioning of the EU (in
Article 107(3)(a)) allows aid that promotes the economic development of areas
where the standard of living is abnormally low or where there is serious
underemployment ('category a' regions). In practice, the areas concerned are
defined as NUTS 2 regions with a GDP per head of less than 75% of the EU-25
average, which broadly correspond to Convergence regions (including Phasing-out
regions). In 2011, aid in these regions amounted to almost EUR 15.2 billion.
Aid in 'category a' regions increased by a
quarter between 2009 and 2011 (from EUR 14 billion), though the longer-term
trend is downwards (from an average of EUR 17 billion in 2003-2005 to EUR 13
billion in 2006-2008). The level of aid in such regions differs between Member
States, reflecting differences in regional policy, the extent to which aid is
used to support development and the size of the eligible population.
Differentiated state aid possibilities for
islands, sparsely populated areas and other regions categorised by geographical
isolation
The Treaty on the Functioning of the EU (in
Article 107(3)(c)) allows aid to be used to facilitate the development of
certain other areas, where it does not significantly affect competition
('category c' regions). The areas concerned include those regions with a GDP
per head below the EU-25 average, those with unemployment over 15% higher than
the national average or those undergoing major structural change or in serious
relative decline, as well as regions with low population density, islands with
a population of 5,000 or less, regions similarly isolated geographically and
regions neighbouring 'category a' regions. Aid in category 'c' regions totalled
around EUR 2.9 billion in 2011 (i.e. just over a quarter of that in 'category
a' regions) and was down by 39% from 2008.
State aid and the Lisbon objectives
The General Block Exemption Regulation (GBER)
was introduced in 2008', giving automatic approval for a range of aid measures
without the need for prior notification. Such a block exemption does not have a
spatial dimension since it applies to all regions. The current GBER will be
extended until the end of 2014 when the Commission will adopt a new GBER,
introducing new categories of aid measure without the need for prior
notification. The GBER covers aid to SMEs, research, innovation, regional
development, training, employment and risk capital, as well as for
environmental protection, entrepreneurship, business start-ups in assisted
regions and issues such as the difficulties of women entrepreneurs to access
finance.
The reform introduced by the GBER was aimed at
redirecting aid towards the Lisbon objectives by encouraging Member States to
focus on assistance that will be of real benefit to competitiveness, job
creation and social and economic cohesion. At the same time, it reduced the
administrative burden for public authorities, aid recipients and the Commission
alike. The GBER unified and simplified previous rules, and enlarged the
categories of state aid covered by the exemption. Almost 41% (EUR 17.2 billion)
of aid to industry and services was already block exempted in 2011 under the
previous regulations as compared with 19% (EUR 11 billion) in 2008 and 6% (EUR
3 billion) in 2006.
Map 1 Regional aid, 2007-2013

5.2.      European
Investment Bank

European Investment Bank loan operations are
directed towards the political priorities established by the EU. The 2013-2015
operational strategy of the EIB combines lending, blending lending with EU
funding, and advisory work to respond to the objectives of EU Cohesion Policy
and Europe 2020. 
The strategy has been updated in response to
the crisis and is focused on (though not limited to) smart growth. The
contribution of EIB is multi-faceted, encompassing support for infrastructure
projects for growth and cohesion including the completion of the TENs and the
deployment of broadband technologies. Supporting SMEs (especially in
knowledge-based activities) is also a central objective, as they are considered
to be crucial for growth, employment and innovation in the EU. The EIB provides
support for sustainable and resource efficient transport, energy efficiency and
renewable energy production as well. 
In response to the crisis the EIB is providing
EUR 60billion additional lending i over the period 2013-2015, increasing the
target for loans given from a EUR 42bn to EUR 62bn in 2013, and EUR 60bn in
both 2014 and 2015. This will enable the Bank to increase its activity in four
priority areas: innovation and skills, SME access to finance, strategic
infrastructure and increased investment to meet the EU's resource efficiency
objectives. 
The European Commission and the EIB have also
developed a number of joint financial instruments where the lending provided is
blended with EU funding to support the pursuit of Europe 2020 targets. These
have a leverage effect on funding and help to increase the impact for final recipients.

In the 2007-13 programming period, around EUR
20bn has been invested in the Structural Programme Loans instrument, which
combines loans with grants. 
The Bank’s activities also include managing the
JASPERS technical assistance facility which provides support to EU Member
States to improve the quality of the major projects submitted for grant
financing by the Structural and Cohesion Funds. From its inception in 2006 up
until the end of 2012, a total of 226 JASPERS-supported projects in 12
countries were approved, involving investment totalling EUR 39bn (EUR 10bn in
2012). 
In addition, the Bank, together with the
European Commission and the Council of Europe Development Bank, set up the
JESSICA initiative (Joint European Support for Sustainable Investment in City
Areas) which is intended to provide reimbursable finance for financing
revenue-generating urban projects through the Urban Development Funds. By the
end of 2012, a total of 75 JESSICA evaluation studies had been commissioned and
18 holding funds had been set up with finance totalling EUR 1.7 billion
covering 54 regions and . 37 Urban Development Funds had been established with
finance amounting to around EUR 1.4bn.
Figure 23 European Investment Bank loans per Member State,
2007-2013
Source: EIB, Eurostat and DG REGIO
calculations

6.     Conclusion

The financial and
economic crisis has led to a severe deterioration of public finance in most EU
Member States. Public deficits increased sharply in 2009 resulting in the
adoption of fiscal consolidation measures across the EU starting in 2010. As a
consequence, public expenditure was reduced in a number of Member States while
the rate of growth was limited in the others. 
The various categories
of public expenditure were not all affected, however, in the same way.
Growth-friendly public expenditure and public investment were particularly
targeted by fiscal consolidation measures, public investment in the EU-27 being
expected to fall to historically low levels in 2014. 
This is particularly
true for subnational levels of government which are responsible for a large
share of growth-friendly public expenditure and public investment. Since 2010,
public investment at sub-national level has fallen significantly in the EU-27,
declining back to 1997 levels. The biggest reduction is in Spain where sub-national public investment fell by 24% a year on average between 2009 and
2012. 
In such a context, the
role of Cohesion Policy in supporting growth-enhancing public expenditure in a
number of Member States has become of major importance and by far the main
source of financing for public investment. Given this, the role of Cohesion
Policy in helping the Member States to pursue a dynamic way out of the economic
crisis and achieve the Europe 2020 objective is becoming ever more crucial. The
tendency for public investment in Member States to be reduced is equally a
concern because it calls into question their ability to respect the principle
of additionality and to co-finance Cohesion Policy programmes in the future.
[1]       Data for Croatia are only available up to 2002.
[2]
Gramlich E., 1994, Infrastructure
investment: a review essay, Journal of Economic Literature, 32(3): 1176-96.
[3]
Blankenau, W.F., Simpson,
N.B., and Tomljanovich, M., 2007, Public Education Expenditures, Taxation,
and Growth: Linking Data to Theory, American Economic Review, 97(2):
393-397.
[4]
Griliches, Z., 1994, Productivity,
R&D, and the data constraint, American Economic Review, 84(1): 1-23.
[5]
Bronzini, Raffaelo and
Eleonora Lachini, 2011, Are incentives for R&D effective? Evidence from
a regression discontinuity approach, Banca d’Italia Working Paper 791.
[6]
European Commission 2012, Report
on Public Finances in the EU.
[7]
Barro, R.J. , 1981, Output
Effects of Government Purchases, The Journal of Political Economy:
1086-1121
Barro, R.J. and Ch. J. Redlick, 2011, Macroeconomic
effects from government purchases and taxes, The Quarterly Journal of
Economics 126 (1):51-102 
Perotti, R., 2005, Estimating the effects of fiscal
policy in OECD countries, CEPR Discussion Paper 4842, Centre for Economic
Policy Research
[8]
Beetsma, R. and M. Giuliodori,
2011, The effects of government purchases shocks: Review and estimates for
the EU, The Economic Journal 121 (550): F4-F32.
Beetsma, R., M. Giuliodori and F. Klaassen, 2008, The
effects of public spending shocks on trade balances and budget deficits in the
European Union, Journal of the European Economic Association 6(2-3):
414-423.
Blanchard, O. and R. Perotti, 2002, An empirical
characterization of the dynamic effects of changes in government spending and
taxes on output, The Quarterly journal of Economics 117 (4): 1329-1368.
Blanchard, O. and D. Leigh, 2013, Growth Forecast
Errors and Fiscal Multipliers, IMF Working Paper 13/1, Research Department,
International Monetary Fund.
[9]           Giavazzi, F., Jappelli, T. and M. Pagano (2000),
"Searching for non-linear effects of fiscal policy: Evidence from
industrial and developing countries", European Economic Review, vol.
44(7).
[10]          Giudice, G., Turrini, A. and J. in’t Veld (2007),
"Non-Keynesian Fiscal Adjustments? A Close Look at Expansionary Fiscal
Consolidations in the EU", Open Economies Review, vol. 18(5).
[11] Di Comite F., Giudice G., Lendvai J. and I. Toming (2012), "Fiscal
consolidation in the midst of the crisis", in EU
Balance-of-Payments assistance for Latvia: foundations of success, European Economy, Occasional Papers 120. 
[12] Aiyagari, S. R.,
L.J. Christiano and M. Eichenbaum, 1992, The output, Employment and interest
rate effects of government consumption, Journal of Monetary Economics 30 (1):
73-86.
Baxter, M. and R. G. King, 1993, Fiscal policy in
general equilibrium, The American Economic Review: 315-334. 
Ramey, V. A. and M.D. Shapiro, 1998, Costly capital
reallocation and the effects of government spending, in Carnegie-Rochester
Conference Series on Public Policy, vol. 48, 145-194.
Cogan, John F, Tobias Cwik, John B Taylor and Volker
Wieland, 2010, New Keynesian versus old Keynesian government spending
multipliers, Journal of Economic Dynamics and Control 34 (3): 281-295.
[13] Auerbach, A. and
Y. Gorodnichenko, 2012a, Measuring the output responses to fiscal policy,
American Economic Journal, 4(2): 1-27.
Auerbach, A. and Y. Gorodnichenko, 2012b, Fiscal
multipliers in recessions and expansions: Fiscal Policy after the Financial
Crisis, NBER Chapters, National Bureau of Economic Research. 
Auerbach, A. and Y. Gorodnichenko, 2013, Output
spillovers from fiscal policy forthcoming in American Economic Review
Papers and Proceedings 103:141-146.
[14] Krugman, P. and
G.B. Eggertson, 2012, Debt, Deleveraging, and the Liquidity Trap: A
Fisher-Minsky-Koo Approach, The Quarterly Journal of Economics (2012) 127
(3): 1469-1513.
[15] Christiano,
Lawrence, Martin Eichenbaum and Gersio Rebelo, 2011, When is the government
spending multiplier large?, Journal of Political Economy 119(1): 78-121
Eggertsson, G. B., 2009, What fiscal policy is
effective at zero interest rates? Staff Report no. 402 Federal Reserve Bank
of New York"
Woodford, M., 2011, Simple analytics of
the government expenditure multiplier, American Economic Journal:
Macroeconomics, 3(1): 1-35
[16] In 't Veld, J. ,
2013, Fiscal consolidations and spillovers in the Euro area periphery and
core, European Economy, Economic Paper no. 506.
[17] Corsetti, G., A.
Meier and G. Müller, 2012, What determines government spending multipliers?,
Economic Policy 27(72): 521–565.
Baum, A., M. Poplaski-Ribeiro and A. Weber, 2012, Fiscal
Multipliers and the State of the Economy, IMF Working Papers 12/286,
International Monetary Fund.
[18]       See European
Commission, 2012, The Quality of Public Expenditures in the EU', Occasional
Papers 125, where spending is analysed on the basis of Eurostat data on the
Classification Of the Functions Of Government (COFOG), Directorate-General
for Economic and Financial Affairs.
[19]          For the sake of this analysis, growth friendly expenditure
correspond to the following COFOG categories: Economic affairs (which mostly
consist of transport and energy), environmental protection, health and
education. Note that R&D is those sectors are included. 
[20]          Data is not available for Croatia in 2008. 
[21]     European Commission, 2012, Report on Public Finances in EMU
2012 – Part IV: Fiscal decentralisation in the EU – main characteristics and
implications for fiscal outcomes, European Economy 4|2012, Brussels. See http://ec.europa.eu/economy_finance/publications/european_economy/2012/pdf/ee-2012-4.pdf.
Governatori, M. and D. Yim, 2012), Fiscal Decentralisation and Fiscal Outcomes,
European Economy, Economic Papers 468 | November 2012, Brussels. See http://ec.europa.eu/economy_finance/publications/economic_paper/2012/pdf/ecp468_en.pdf.

[22]     Data for Croatia in 1995 is not available.
[23]    Transport and communications are included as part of ‘Economic
affairs’ in the COFOG classification of expenditure, which also includes
support to enterprises.
[24]     For example, healthcare in Denmark or Sweden. Note that earmarked transfers are not the general norm and often co-exist with
general transfers.
[25]     Defined as the sum of Gross Fixed Capital Formation of the
General Government and capital transfers paid by the public sector. 
[26]     Data for Croatia is only available from 2002.
[27]     In many instances, revenue from local taxes is largely
controlled by central government which sets limits on the tax rates that can be
imposed.
[28]     Note that, because of transfers between various levels of
government, the extent of public deficit at the sub-national level should not
be interpreted as their contribution to the general government deficit. 
[29]     Total public capital investment is equal to the sum of public
fixed investment (Gross Fixed capital formation of the General Government) and
capital transfers paid by the general government. Please note that the
percentages reported have to be considered as ratios, as the expenditure
co-financed by SF is not entirely captured by the two public investment
indicators proposed in this section. Capital transfers include capital support
to financial institutions. 
[30]     Under the principle of additionality, Member States commit to
avoid replacing national funding with EU funds and to maintain a certain level
of spending on public investment.
Chapter 5: 
The importance of good governance for economic and social development

1.     Why
should the EU focus on good governance?

There are two opposing views among
economists of the link between good governance and economic and social development.
The first sees good governance as a by-product of development. The second regards
s good governance and efficient institutions as a necessary condition for
strong economic and social development. It considers that countries can remain
stuck in a low-growth, low-quality institutional equilibrium and that a shock may
be needed to move them out of it (Acemoglu 2012[1]).

A growing body of research endorses the
second view and emphasises the beneficial effect that efficient institutions
can have not only on economic growth but also on innovation and
entrepreneurship, health, well-being and the reduction of poverty as well as on
the impact of Cohesion Policy (Rothstein 2011, Rodriguez-Pose 2012, OECD 2013[2]). As a result, it is now widely accepted that 'high-quality, reliable
public services and legal certainty (are) a major precondition for economic
success' and that '... weak administrative and judicial capacity as well
as legal uncertainty constitute key impediments in addressing economic
development challenges.'[3]
One of the major aims of the process
involved in accession to the EU is to ensure that the rule of law, equality
before the law and non-discrimination are firmly entrenched in the legal
framework and practices of the countries applying for entry. These conditions
for membership continue to apply after accession and all governments are
expected to make sure that they do so. 
At a time when Member States are facing
increasing pressures on public budgets, the challenge of ensuring high-quality
public services requires technological and organizational innovation to boost
efficiency. This applies both to delivering public services and designing and
implementing high quality public investments. 
Good governance, legal certainty and high
quality regulations are essential for a stable business environment. The
institutions that govern economic and social interactions within a country need
to fulfil a number of key criteria. These include the absence of corruption, a
workable approach to competition and procurement policy, an effective legal
environment, and an independent and efficient judicial system. Moreover,
strengthening institutional and administrative capacity, reducing the
administrative burden and improving the quality of legislation underpins
structural adjustments and fosters economic growth and employment[4].
The modernisation of public administration
was one of the five policy priorities identified in the Annual Growth Survey in
2012, 2013 and 2014[5] since it is seen as a key requirement for the success of the Europe
2020 agenda. The reform of public procurement, digitisation of public
administration, reduction of the administrative burden falling on individuals
and SMEs and increased transparency are regarded as part of such modernisation[6]. Emphasis is also given to the fight against corruption and
improving both public authorities and the judiciary. 
This chapter provides an overview of the
performance of public institutions in general focussing on the ease of doing
business, corruption and governance at the national and regional level and
concludes by highlighting the link between good governance and the implementation
of Cohesion Policy.
Box on definitions of Good governance
There are a number of different ways of
defining and identifying good governance. A relatively straightforward one
focusses on the ease of doing business. This is the case of the World Bank's
Doing business reports, which argue that governments can facilitate economic
growth by providing a simple and transparent regulatory system, so that businesses
can concentrate on their core activities and need only to devote a fraction of
their resources to complying with administrative procedures. 
Transparency International, on the other
hand, focusses primarily on corruption, which is defined as the abuse of
entrusted power for private gain. Corruption, it is argued, hurts anyone who
depends on the integrity of people in authority and goes well beyond limiting
economic development to damaging health, trust and well-being.
A more targeted approach is adopted by Bo
Rothstein (2011), who argues that good governance means the impartial exercise
of public power. This focuses on how policies are implemented rather than on
their substance as such and clearly means that there is no place for
corruption, ‘clientelism’, favouritism, discrimination and nepotism. The
benefit of such a focussed approach is that it facilitates monitoring and
targets interventions on ensuring that public institutions operate impartially.

A broader approach is taken by the
Worldwide Governance Indicators, also published by the World Bank, which
defines governance as "the traditions and institutions by which
authority in a country is exercised. This includes (a) the process by which
governments are selected, monitored and replaced; (b) the capacity of the
government to effectively formulate and implement sound policies; and (c) the
respect of citizens and the state for the institutions that govern economic and
social interactions among them"[7].
A new European regional indicator combines
the approaches of Rothstein, Transparency International and the World Bank,
taking account of regional survey results that capture people’s experience of
corruption and the impartiality of public services as well as national level
Governance indicators 
Although the differences in definition are
salient, the results generated by the different measures are highly correlated
which indicates that they all tend to capture the same deficiencies in
governance.

2.     Doing business is easier in the North of the EU

Good business regulation allows companies
to focus their time and energy on doing business without losing time on
complying with red tape. The best countries to do business in are not the ones
without rules and regulations but those where these are clear and easy to
comply with. 
The World Bank’s "Doing Business"
indicator is based on the notion that regulations should be 'S.M.A.R.T' -
Streamlined, Meaningful, Adaptable, Relevant and Transparent. The indicator
combines 10 aspects[8] to assess the way that business regulations affect SMEs in 189
counties and essentially measures their complexity and the costs they impose as
well as the strength of legal institutions. 
According to the indicator, Denmark is rated as the most 'business-friendly' country in the EU (in 5th place overall)
and Malta the least friendly (in 161st place)[9].
The 10 most business-friendly Member States (all in the top 30 worldwide) are
the three Nordic countries, the three Baltic States, the UK, Ireland, Germany and the Netherlands. The five least friendly are Malta, Croatia, Czech Republic, Romania and Greece. 
Important elements included in the
indicator are the amount of time, the number of procedures and the costs and
capital needed to start a business. In the EU, this requires an average of 13
days and 5.4 separate procedures and costs the equivalent of 4.4% of national
income per head with minimum paid-in capital amounting to 10% of the latter.
The difference between Member States is substantial. In Lithuania and Ireland, half the number of procedures are required at a fraction of the cost compared
with the Czech Republic and Malta (Table 1). 
Table 1 Starting
a business in 2014
 Country || Rank || Procedures (number) || Time (days) || Cost (% of income per capita) || Paid-in Min. Capital (% of income per capita) 
 Lithuania || 11 || 4 || 6.5 || 0.9 || 0 
 Ireland || 12 || 4 || 10 || 0.3 || 0 
 Czech Republic || 146 || 9 || 19.5 || 8.2 || 29.5 
 Malta || 161 || 11 || 39.5 || 10.8 || 1.5 
 EU-28 || 70 || 5.4 || 12.9 || 4.4 || 10.4 
Source: Doing Business 2014, World Bank

Box Ease of doing business varies within
a country

The World Bank now assesses the ease of
doing business in different locations in a growing number of countries. The variation
in Italy, in particular, is marked. For example, to obtain the construction
permits to build a warehouse requires 164 days in Bologna at a cost equivalent
to 177% of income per head but 208 days in Potenza at a cost of 725% of income
per head. Enforcing a contract takes an average of 855 days and costs 22% of
the claim in Turin as compared with 2022 days and a cost of 34% of the claim in
  Bari. Starting a business varies from 6 days in Padua to 16 days in Naples,
while registering a property takes 13 days in Bologna but 24 days in Rome.
Figure 1: WB
Doing Business, 2006-2014
Between 2006 and 2014, all Member States
improved their position in relation to the ideal as regards the ease of doing
business (measured as 100 in Figure 67, i.e. where the best approach is adopted
for all aspects). The biggest improvements occurred in a number of the
countries furthest from the ideal - Croatia, Poland, Czech Republic and Slovenia, though Portugal, France and Romania also showed large improvements. 
The ease of doing business, however, also
varies between places within countries as a result of differences in the way
national regulations are implemented (see Box). There is a need, therefore, to
reduce differences in the ease of doing business not only between countries but
also between regions or cities within countries.
 Box on E-Government and public e-Tendering can improve the ease of doing business and reduce costs E-Government allows public authorities to provide services more transparently and more cost-effectively. The EU’s Digital Agenda for Europe includes the goal of increasing the use of e-Government services to 50% of EU citizens by 2015. In 2012, 44% of the population in the EU made use of e-Government services. Between 2011 and 2012, the share increased in all but three countries (Figure 68). The increases were biggest in Romania (+24 percentage points), Croatia (8 percentage points) and Greece (7 percentage points), but the overall shares remain small. Italy had the smallest share of people using e-Government services in 2012 (18%), which was smaller than in 2011 Figure 2 e-Government usage by citizens, 2011-2012 Source: Eurostat E-procurement The adoption of e-procurement – the use of electronic communication by government to buy supplies and services or to tender for public works – can generate significant savings for European taxpayers. As part of the modernisation of European public procurement, the Commission has accordingly proposed to make e-procurement the standard method in the EU by mid-2016. Despite the benefits, e-procurement is still in its infancy in the EU. It was used in only 5-10% of procurement procedures in 2012 and only 12% of enterprises across the EU used the Internet when tendering. In only four Member States (Ireland, Lithuania, Slovakia and Poland) was the proportion above 20% Figure 3 Enterprises using the internet in public e-Tendering, 2012 Source: Eurostat 

3.     Most
Europeans think corruption is wide spread and a
major problem

The recent EU Anti-Corruption report[10] emphasises that corruption affects all Member States, but that it
cannot be addressed by a one-size-fits-all policy because of the big difference
in the nature and extent of corruption between Member States. Corruption harms the Union as a whole. It distorts the single market,
reduces public finances and lowers investment levels. The issue is particularly
relevant for cohesion, since less developed regions and Member States tend to
score poorly on corruption and governance indicators.
The majority of the EU population see
corruption as a major problem in their country (see figure). In all but five
Member States (the Nordic countries, the Netherlands and Luxembourg), over 60%
of people see corruption as a major problem, the proportion varying between 61%
(in Germany) and 99% (in Romania).
Figure
4: Corruption is a major
problem, 2011
In 2013, four out of five people in the EU
considered that corruption was widespread in their country. As in 2011, the
Nordic countries had the lowest perceptions of corruption. In half of the
Member States, nine out of ten people thought that corruption was widespread or
very widespread. 
The perception of corruption, however, can
be heavily influenced by recent political scandals or
by the financial and economic situation, which is less the case for direct
experience of corruption or witnessing it at first hand. Only 8% of people in
the EU surveyed had experienced or corruption or witnessed it in the previous
twelve months. The figure, however, was significantly higher in 9 Member
States, ranging from 12% in Cyprus to 25% in Lithuania.
Figure
5 How widespread is
corruption in your country, 2013
Despite the view that corruption is
widespread and problematic, in a global perspective most EU Member States score
relatively well on the Corruption Perception Index[11] (CPI), created by Transparency International[12] and covering 177 countries. The top 20 least corrupt countries according
to the 2013 index include 8 EU Member States (the three Nordic Member States, the Benelux countries, Germany and the UK). Seven Member States, however, have
relatively low scores and are ranked between 57 and 80. These, in descending
order, are Croatia, the Czech Republic, Slovakia, Italy, Romania, Bulgaria and Greece. 
Map
1: Corruption Perception Index,
2012
In addition, the study Identifying and
reducing corruption in public procurement in the EU[13], commissioned by the European Commission at the request of the
European Parliament shows that about 20% of the GDP of the EU is spent through
public procurement (EUR 2.4 trillion at 2010 prices). Given these figures, the
EU anti-corruption report concluded that public procurement is a hot spot for
corruption. The study focussed on a number of areas in which considerable
amounts of EU funding are spent through public procurement, in particular road and
rail transport, water and waste management, urban and public utility
construction and training. Table 20 shows the estimated effect of corruption in
these areas.
Table 2 Estimated direct costs of corruption in
public procurement
 Direct costs of corruption in public procurement 
   || Direct costs of corruption (in million EUR) || % of the overall procurement value in the sector in the 8 Member States 
 Road & rail || 488 –755 || 1.9 % to 2.9% 
 Water & waste || 27 –38 || 1.8% to 2.5% 
 Urban/utility construction || 830 - 1 141 || 4.8% to 6.6% 
 Training || 26 –86 || 4.7 % to 15.9% 
 R&D || 99 –228 || 1.7% to 3.9% 
Corruption varies between policy areas, some
being more prone to fraud than others. Training is the most vulnerable, the estimated
loss of public funds from corruption ranging from just under 5% of the total
spent to almost 16%. 
The study also examined several types of indicator
– or ‘red flags’ – which signal corruption, the most common one being bid
rigging where competitors collude to ensure that one of them wins the contract
being tendered. In the case of training, the most common ‘red flag’ are kick-backs,
or payments to the public officials awarding the contract. A conflict of
interest in procurement occurs when public officials or their family members
own shares in the winning company. If a public official ignores that a
contractor overtly does not execute a required task, this is considered as
deliberate.
Table 3 Type of
corruption by policy area
   || Bid rigging || Kick-backs || Conflict of interest || Deliberate Mismanagement 
 Urban/utility construction || 19 || 14 || 11 || 3 
 Road & Rail || 10 || 8 || 4 || 1 
 Water & Waste || 15 || 6 || 3 || 0 
 Training || 1 || 3 || 2 || 1 
 R&D || 12 || 4 || 2 || 0 
 Total* || 57 || 35 || 22 || 5 
The study also concluded, however, that
EU-funded projects are less prone to corruption because of the management and
control systems which are required to be implemented and the anti-fraud
measures covering EU-funded expenditure.

Box: Ways of
tackling corruption 

A recent study by ANTICORRP, which analysed corruption in Romania, Hungary and   Estonia, underlines the fact that an anti-corruption policy to be effective
needs to be part of a broader strategy of improving governance. Repression,
special legislation or an anti-corruption agency does not by itself
automatically have a significant impact on corruption. Nor is it easy for an
outside body to do much directly though it can help to influence things.
A good starting-point for reducing corruption is to reduce the
administrative opportunities for discretionary behaviour. E-Government and
public e-tendering can help in this regard, as can administrative reforms to
cut red tape and streamline regulations. Improving the ease of doing business
can, therefore, also help to combat corruption in part by limiting the
opportunities for it to occur.
The participation and cooperation of the private and voluntary sectors
can increase the social pressure against corruption. Concerned individuals can
also help to maintain an independent judiciary and a high level of public
accountability. The media are particularly important since they can act as a
watchdog over governance, though they need to be economically independent and
pluralistic to do so.

4.     Governance indicators vary between
and within EU Member States 

The World Bank Governance Indicators, which
cover over 200 countries, consist of six measures: Political stability,
Government effectiveness, Regulatory quality, Rule of law, Control of
corruption and Voice and accountability. 
The indicator of Government
effectiveness (which measures public perception of the
government’s capacity to provide high standard public services, the efficiency
and independence of the civil service and the ability to manage the creation
and implementation of public policies), is especially relevant for economic
development and varies considerably between EU Member
States (Figure 72). It shows the three Nordic countries
as having the most effective governments and Romania, Bulgaria, Greece and   Italy as having the least effective. It also shows little change for most
Member States between 1996 and 2012 and an improvement in Lithuania, Bulgaria,  Latvia and Croatia, if from a low starting-point. It shows, however, a
significant deterioration in government effectiveness in Greece and Spain, which might be a result of the economic crisis
The ‘Rule of law’ indicator, which measures
public perception of how laws are implemented and how well they are enforced,
also varies between Member States and in a very similar way to how government
effectiveness is perceived. The three Nordic countries have again the highest
scores and Romania, Bulgaria, Greece and Italy the lowest, along with Croatia. There are similarities as well in the changes which occurred between 1996 and
2012, with significant improvements in Bulgaria and Croatia – though the score
in both remaining low – as well as in the three Baltic States, and a
significant deterioration in Greece and Spain, as well as in Italy.
Figure 6: World
Bank, Government effectiveness and Rule of Law, 1996-2012
  

4.1.      Some regions have a far higher
(or lower) quality of government

As indicated above, there are variations across
regions in the way that national regulations are implemented, which reflect
differences in the efficiency of regional and local authorities. These
differences are also important to take into account when assessing the quality
of governance in relation to economic and social development. 
A new regional index, constructed by the
Gothenburg Institute of Quality of Government, enables this to be done. The
results are disturbing, in that 15% or more of respondents in many regions in Bulgaria, Romania, Hungary and Italy report that they had personally paid a bribe in the preceding
12 months. The perceived quality of government varies markedly between regions
in Italy, Spain, Belgium, Romania and Bulgaria. In the first three, it was
rated to be lowest in the less developed regions, implying perhaps that they
may be stuck in a low-administrative quality, low-growth trap. In Romania and Bulgaria as well as Hungary, the capital city region was more poorly rated than others,
reflecting perhaps the greater opportunities for corruption there. 
In the countries with the highest perceived
quality of government - the three Nordic countries and the Netherlands – there were no great differences between regions. 
The situation in the outermost regions differs
between countries. While the Portuguese ones are rated the same as the national
average (Acores) or higher (Madeira), the Spanish (Canarias) and the four
French ones are rated below. 
The results of the 2013 survey are much the
same as for 2010[14],
which, when it was published, spurred a lot of research on the link between the
quality of government in regions and their rate of innovation, entrepreneurship
and growth. Some of the key findings of this research are set out in the OECD
2013 report Investing Together, which concluded that a low quality of
government hinders economic development and reduces the impact of public
investment. This applies equally to the investment co-financed under Cohesion
Policy, implying that its effect on regional development could be enhanced by
improvements in the quality of governance. Such improvements, however, will not
necessarily come about merely through the passage of time but are likely to
require concerted efforts at all levels of government as well as the active
involvement of the public and the media. 
 Box How does European quality of Government index constructed? This index, commissioned by DG Regional and Urban Policy and first published in 2010, combines World Bank Governance indicators at the national level with a survey that captures regional variations within each country. As a result, the national average of the regional indices equals the World Bank Governance score. It has been updated to 2013 with the support of the 7th Framework Programme[15]. The survey focuses on the public services which are often controlled locally or regionally (law enforcement, education and healthcare) and which are more likely to vary between regions. Questions cover the quality and the impartiality of these services as well as the perception and personal experience of corruption. The questions[16] include among others: –   How would you rate the quality of public education in your area? –   Certain people are given special advantages in the public health care system in my area –   All citizens are treated equally by the police force in my area –   . In the past 12 months have you or anyone living in your household paid a bribe 
Map
2 European Quality of
Government index, 2013

4.2.      The authority of EU regions is growing

There is a trend towards regionalisation in many
parts of the EU. According to the regional self-rule index (see Box), regions
in many Member States have become more autonomous over the past 50 years,
especially in Italy, Belgium and Spain as well as Scotland in the UK, in all of
which there were high levels of self-rule at regional level. 
The degree of self-rule also increased
substantially in regions in the Czech Republic, Slovakia, Poland, Greece and Finland but, nevertheless, remained relatively low. 
In German and Austrian regions, there were only
minor changes, though the high level of self-rule was already high in 1960. No
real change occurred in regions in England, Sweden, mainland Portugal, Croatia and Bulgaria (Map 79). 
In 2011, the regional self-rule index was
highest in the Federal States of Germany, Austria and Belgium. It was second highest in 'Regional States', which are more centralised than
federal ones, but less so than unitary ones. It was particularly high in the most
autonomous regions, such as Ǻland in Finland, Scotland in the UK, Navarra in Spain and Açores and Madeira in Portugal. The index was lowest in Bulgaria, mainland Portugal and Ireland[17].
In addition to the degree of self-rule, the regions
covered by the index also differ in the size of their population. In Germany, France, Italy, Spain and Poland, all or virtually all the regions have a population of over
one million. In the UK, however, as well as in Bulgaria, Croatia and Finland, the majority of regions distinguished have a population below 250 000. 
In 2011, regions in around half the Member
States had some autonomy over borrowing. It was greatest in the German Länder
and the Italian regions, which in both cases can borrow without restriction,
while regions in France, the Netherlands, Hungary and Sweden, as well as Scotland, can borrow without prior authorisation of the central government but
within specified limits. For regions in the Czech Republic, Croatia, Poland, Romania, Spain and England, as well as for Wales, borrowing requires both prior
authorisation and is limited in amount. In the other 9 Member States which have
regions, these are not able to borrow at all. 
In 2011, only Navarra and the Basque provinces
in Spain had a high level of fiscal autonomy, in that they were able to decide
the base and the rate of at least one major tax (personal income, corporate,
value added or sales tax). A few other regions (the other Spanish regions,
Belgian and Italian regions, Åland in Finland, Açores and Madeira in Portugal, the Län in  Sweden and Scotland) were able to set the rate of at least one major tax, if
within limits, but not the base. The German Länder were able to decide the base
and the rate of minor taxes, while regions in Croatia, France, Hungary, Italy,
Netherlands, Romania, Slovakia and England were able to set the rate, but not
the base. 
In Bulgaria, Czech Republic, Denmark, Finland
(apart from Åland), Greece, Hungary, Ireland, Poland, mainland Portugal,
Romania, Northern Ireland and Wales, the base and the rates of all local or
regional taxes are set by central government.
The regional self-rule index covers the changes
up to 2011 and shows that the crisis has had an effect on this. In some cases,
regions have been granted more powers and responsibilities, while in other cases
central governments have increased their control over regional authorities, by,
for example, limiting their capacity to borrow money. 
A point to note, however, is that the index
does not capture the full extent of decentralisation as it does not measure the
degree of self-rule of local authorities. Given the growing role of cities and
metropolitan areas in governance, this is an aspect which the Commission
intends to investigate further. 
 Box: The regional self-rule index The index captures the area over which a government exercises authority, the extent of this (degree of independence) and the spheres of action over which it is exercised. The territorial scope of authority distinguishes self-rule (a government exercising authority within its own jurisdiction) and shared rule (a government co-exercising authority over a larger jurisdiction of which it is a part). The extent of authority measures the degree to which a government has independent legislative, fiscal and executive responsibility, the conditions under which it can act unilaterally and its capacity to override central government decisions. The spheres of action indicate the range of policies over which a regional government has authority – taxation, borrowing and constitutional reform, in particular. The regional self-rule index covers five dimensions (see table). Table 4 Dimensions of regional authority (self-rule) Self rule || The authority exercised by a regional government over those who live in the region 
 Institutional depth || The extent to which a regional government is autonomous rather than appointed by the national government 
 Policy scope || The range of policies for which a regional government is responsible. 
 Fiscal autonomy || The extent to which a regional government can independently tax its population. 
 Borrowing autonomy || The extent to which a regional government can borrow 
 Representation || The extent to which a region has an independent legislature and executive 
 Source: Hooghe, Liesbet, Gary Marks, Arjan H. Schakel, Sandra Chapman, Sara Niedzwiecki, Sarah Shair-Rosenfield (forthcoming). Governance Below the State: Regional Authority in 81 Countries. Oxford: OUP. 
 Map 3 Regional self-rule index, 2011 || Map 4 Change in regional self-rule index, 1960-2011 
 Box: OECD Principles: Effective public investment: A shared responsibility across levels of government The OECD has recently approved a set of principles for public investment which, for the first time, cover sub-national governments, so recognising the important and growing role of regional and local authorities in planning and implementing public investment. The recommendations need to be seen in the context of the crisis, which has reduced public investment in many countries and put more emphasis on ensuring value for money. These principles will be monitored every three years by the OECD committees and though not legally binding, they have some moral force. Effective public investment requires close co-ordination across levels of government to bridge information, policy or fiscal gaps which may occur. It also requires the capacity at different administrative levels to design and implement public investment projects. The principles, therefore, relate to how to coordinate public investment across levels of government, how to strengthen the capacity to carry it out and how to ensure a sound framework for planning it. Since public investment projects are rarely planned, financed and implemented by a single authority, different levels of government at various stages of the process are involved which accordingly need to work together. Public investment also tends to require involvement at local level even when carried out by central government since it is essential to take account of local needs, possible bottlenecks and particular territorial factors if it is to be effective. Accordingly, even if they have no funding or decision-making responsibilities, local authorities can increase (or reduce) its results and impact. To help countries address these challenges, the OECD has developed a set of Principles on Effective Public Investment Across Levels of Government. The goal is to help governments at all levels to assess the strengths and weaknesses of their public investment capacity and to set priorities for improvement. The Principles are combined into three groups, which represent systemic multi-level governance challenges for public investment: a)   Co-ordination challenges: Cross-sector, cross-jurisdictional, and intergovernmental co-ordination is necessary but difficult in practice. The constellation of actors involved in public investment is large and their interests may need to be aligned. b)   Capacity challenges: Where the capacity to design and implement investment strategy is weak, policies may fail to achieve their objectives. Evidence suggests that public investment and growth outcomes are correlated with the quality of government, including at the sub-national level. c)   Challenges in framework conditions: Good practice in budgeting, procurement and regulation is integral to successful investment but is not always consistent across levels of government. OECD Principles on effective public investment across levels of government OECD Member countries should take steps to ensure that national and sub-national levels of government use resources for public investment on territorial development effectively, in accordance with the Principles set out below: Coordinate public investment across levels of government and policies ·   Invest using an integrated strategy tailored to different places. ·   Adopt effective means of coordination across national and sub-national governments. ·   Co-ordinate among sub-national governments to invest at the relevant scale Strengthen capacity for public investment and promote policy learning across levels of government ·   Assess upfront the long-term effects and risks of public investment. ·   Encourage stakeholder involvement throughout the investment cycle. ·   Mobilise the private sector and financing institutions to diversify sources of funding and strengthen capacity. ·   Reinforce the expertise of public officials and institutions throughout the investment cycle. ·   Focus on results and promote learning. Ensure sound framework conditions for public investment at all levels of government ·   Develop a fiscal framework adapted to the investment objectives pursued. ·   Require sound, transparent financial management. ·   Encourage transparency and strategic use of public procurement at all levels of government. ·   Strive for quality and consistency in regulatory systems across levels of government. More information at: http://www.oecd.org/gov/regional-policy/oecd-principles-on-effective-public-investment.htm 

5.     Poor Governance limits the impact of Cohesion Policy

A lower standard of governance can affect the
impact of Cohesion Policy both directly and indirectly. In the first place, it
can reduce expenditure if programmes fail to invest all the funding available.
Secondly, it can lead to a less coherent or appropriate strategy for a country
or region. Thirdly, it may lead to lower quality projects being selected for
funding or to the best projects not applying for support at all. Fourthly, it
may result in a lower leverage effect because the private sector is less
willing to co-finance investment.
A poor quality governance system is not the
same as one which is corrupt or fraudulent, although it may be both. Nor does
it necessarily involve illegalities. A slow decision-making process, badly
organised public consultations, a focus on short-term electoral gain over a
longer-term development strategy and frequent changes in policies and
priorities can be perfectly legal but they, nevertheless, tend to undermine the
impact of Cohesion Policy. 

5.1.      Poor governance can slow down
investment, leading to funding losses

According to the latest data available (21 May
2014), Member States, on average, had absorbed (or spent) only 68% of the EU
funds available for the 2007-2013 period[18]. Romania had absorbed only 46% of funds and Slovakia, Bulgaria, Italy, Malta and the Czech Republic, less than 60%. By contrast, Finland, Estonia, Latvia and Portugal had absorbed over 80%. The slow rates of absorption in the
countries concerned could be due to a number of reasons, not least a lack of
competence in Managing Authorities, or Governments more generally, or
insufficient staff. Whatever the reason, it could mean that Member States are
unable to spend the funding available to them in the time allowed and
accordingly lose some of it (under the decommitment, or ‘n+2’, rule) or spend
the funding inefficiently in an attempt to spend it in time.
Relating the rates of absorption of funding to
the World Bank Government effectiveness index suggests that there may be a link
(Figure 73). Seven Member States are below average for both government
effectiveness and absorption (EU-27 average is 68%), while 10 are above average
for both. On the other hand, Estonia, Lithuania and Portugal have the highest
absorption rates but a government effectiveness rate which is below average, if
only just. It is possible that being small and having a limited number of Managing
Authorities facilitates achieving a high absorption rate, though this does not
seem to have helped Malta or Latvia. 
Figure 7 Cohesion Policy funding absorption and Government
effectiveness, 2014
Sources: World
Bank and SFC
Many of the difficulties of managing Cohesion
Policy programmes are of an administrative nature related to human resources,
management systems, coordination between different bodies and the proper
implementation of public procurement. Overall staff numbers vary widely between
Managing Authorities, which differ too in the extent to which they rely on
in-house as opposed to outside staff and whether there are dedicated or partially-dedicated
personnel in particular roles (managing, certifying, auditing and
implementing). 
Problems caused by simply not having enough
appropriately qualified personnel can be long-term and systemic (as in Bulgaria or Romania, for example) or temporary (as in the case of auditing in Austria). High turnover of staff is a recurrent problem at all administrative levels, particularly
in some EU-12 countries. In several countries, funding for technical assistance
is used to pay salaries or even bonuses to strengthen particular functional
areas (which has prompted the launching of a study by the Commission to clarify
the situation). 
The adoption of modern management systems to
provide incentives for good performance and to hold managers accountable for
results is patchy. In some countries, systems to avoid conflicts
of interest or prevent corrupt practices by public officials are weak.
Computerised methods to improve efficiency and transparency in the use of EU
funds are well developed in a number of countries but almost non-existent in
others. In general, financial monitoring and control systems function well, but
those monitoring outcomes and results work less well, though there are several
examples of good practice which can be built on in the present programming
period. 
Strategies developed to meet EU policy
objectives are sometimes not adhered to because of political pressure. In some
countries, particular efforts are needed to strengthen both project pipelines
(selection criteria, project preparation and tendering) and implementation
(contracting and project management). 
In a number of Member States, it has proved
difficult to carry out major projects within the time limits set for
expenditure to be eligible for co-financing. A common problem is that regional
and local authorities have limited capacity to prepare and implement complex
projects, so that efforts to build capacity need to be targeted at all
administrative levels and not just the national.
Systematic weaknesses in all aspects of public
procurement are the single most common cause of the irregularities found during
audit, resulting in suspension of payments and financial correction. Several
Member States have demonstrated limited capacity to implement the Environmental
Impact Assessment and Strategic Environmental Assessment Directives as well as
to apply State Aid rules correctly, with EU-12 countries usually requiring more
support (which is also likely to be the case for Croatia in the new period).
Frequent problems occur, in particular, in respect of railways, solid waste,
wastewater, RTDI, ICT and financial instruments. 
Problems of coordination can occur between
different national horizontal (i.e. sectoral) programmes as well as between
national and regional programmes. In addition, the delegation of tasks by Managing
Authorities to intermediate bodies can become overly complex and dilute
accountability.

5.2.      Poor governance can reduce the
leverage effect of Cohesion Policy

Spending the funding available is a necessary
but not sufficient step for achieving a strong impact of Cohesion Policy. This
also depends on what the funding is spent on, whether the projects concerned
deliver value for money and whether there is general confidence that they will
be completed.
The skill and intent of the politicians and the
national and regional authorities responsible for managing the funds are
important here. The lack of skills can be overcome by training and hiring more staff, so long as the
need to do so is recognised (Rodríguez-Pose and
Storper, 2006[19]). The deliberate intent of a government
and/or an authority to pursue goals other than providing the public goods and
services needed by people is more difficult to combat – a situation described
by Barca (2009[20]) as state capture. 
High quality governance creates a virtuous
cycle, in which people trust the government to make the right choices and to
spend their taxes in the most cost-effective way which leads to wide
participation in public calls for tender, so keeping down costs, and to
business investment taking account of government policy (Acemoglu et al.,
2012). 
Low quality governance, on the other hand,
creates a vicious cycle, in which trust in government breaks down, taxes are
evaded, corruption is no longer reported, participation in public calls for
tender declines as businesses assume they need the right connections or bribes
to get contracts and the climate for investment is uncertain because of the
unpredictability of government policy. To break such a vicious cycle, an
outside shock or external support for local forces seeking to improve the
quality of governance is often needed.
Recent empirical research (Rodriguez-Pose and
Garcilazzo 2014[21]) shows the important role of the quality of government as a direct
determinant of economic growth as well as a moderator of the efficiency of Cohesion
Policy expenditure. According to the findings of the research, improving the
quality of government in lagging regions is a fundamental precondition for
increasing the impact of Cohesion Policy (see Box). The greater emphasis in the
new programming period on improving the administrative capacity to manage
funding and making this a condition for receipt of support is in line with
this..
Box: The quality of government as a determinant of the effectiveness
of Cohesion Policy
In a recent study carried out by Rodriguez-Pose and Garcilazzo
(2014), real growth of GDP per head between 1995 and 2006 in EU-15 regions was
analysed with the aid of an econometric model using panel data analysis. The
aim was to identify the underlying determinants and to assess the role of i
Cohesion Policy expenditure, the quality of government and the interaction
between the two. The results indicate that expenditure had a significant impact
on the growth of GDP per head and in the regions that received a substantial
amount funding (mostly the less developed ones) the higher the quality of
government, the greater the impact. 
They also suggest that low quality of government is an obstacle that
cannot be overcome by increasing spending and that improving the quality of
government is essential for Cohesion Policy to have its full impact. 

6.     Conclusion

The ease of doing business, the level of
corruption and the quality of governance varies substantially across EU Member
States and regions. This limits the growth potential of those where governance is
below average and hinders the proper functioning of the single market. Many
people in the EU are seriously concerned about corruption even in countries
with a good reputation for combating it and limiting the abuse of public power.

A wide range of indicators suggest that in
a number of Member States (in the EU-15 as well as the EU-13) and regions,
especially the less developed ones, the system of governance is of low quality,
which hinders social and economic development and limits the impact of Cohesion
Policy. The regional dimension of governance is of increasing importance in
many parts of the EU as the authorities concerned acquire more autonomy and
more responsibility for public expenditure. The principles of effective
investment developed by the OECD in recognition of the major role of local and
regional authorities in this respect indicate how the most impact can be
obtained from investment spending.
The Commission along with the OECD and
other international organisations has recognised the importance of improving
governance at all levels across the EU and has taken steps on several fronts to
this end, including through the new anti-corruption report and a stronger
emphasis on this in the annual growth survey and in Cohesion Policy in the new
period (see next chapter).
[1]
Acemoglu D and Robinson J., 2012, Why Nations Fail: The Origins of Power,
Prosperity, and Poverty, Random House LLC, 2012, ISBN 0307719235,
9780307719232.
[2]
Rothstein B., 2011, The Quality of Government: Corruption, Social Trust, and
Inequality in International Perspective, University of Chicago Press, ISBN 0226729575, 978022672957
Rodriguez-Pose,
A. and E. Garcilazo 2013, Quality of Government and the Returns of
Investment: Examining the Impact of Cohesion Expenditure in European Regions,
OECD Regional Development Working Papers, No. 2013/12, OECD Publishing.
[3]       European Commission, SEC(2010) 1272.
[4]       The World Economic Forum's Global Competitiveness report has
"quality of institutions" as the first pillar of assessment.
[5]       The 2013 Annual Growth Survey and the Economic Adjustment
Programmes highlighted the link and stressed the need for Member States to
increase the efficiency and effectiveness of public services as well as the
transparency and quality of public administration and the judiciary. 
[6]       Communication COM(2013) 453 final “End-to-end e-procurement
to modernize public administration”.
[7]     The Worldwide Governance Indicators: Methodology and Analytical
Issues. Daniel Kaufmann, Brookings Institution Aart Kraay and Massimo
Mastruzzi, World Bank
[8]     These are starting a business, dealing with construction,
enforcing contracts and resolving insolvency, getting electricity, registering
property, getting credit, protecting investors, paying taxes, trading across
borders.
[9]     World Bank, Doing Business 2014.
[10]       European
Commission, 2014, EU Anti-corruption Report, COM (2014) 38
[11]     This index averages the standardised scores of up to 13 surveys
of citizens and businesses on the perception of corruption in the public
sector. A high score means a low perception of corruption. 
[12] As also mentioned in the study 'Public Procurement: costs we pay
for Corruption' (http://ec.europa.eu/anti_fraud/documents/anti-fraud-policy/research-and-studies/identifying_reducing_corruption_in_public_procurement_en.pdf).
[13] http://ec.europa.eu/anti_fraud/documents/anti-fraud-policy/research-and-studies/identifying_reducing_corruption_in_public_procurement_en.pdf

[14]     Due to slight changes in the methodology the two surveys are
not fully comparable. 
[15]     It is based on a survey of 85 000 respondents covering 24
countries and 212 regions. See ANTICORRP www.anticorrp.eu.
[16]     See http://nicholascharron.wordpress.com/european-quality-of-government-index-eqi/
for more info.
[17]     The three Baltic States, Luxembourg, Slovenia, Cyprus and Malta did not have regions in 2011 according to the regional definition used by the
researchers (average population of min 150 000).
[18]     In the sense of claiming and receiving payment for expenditure
carried out under the Structural Fund and Cohesion Fund programmes. These
figures include advance payments.
[19] Rodríguez-Pose A. and Storper, M., 2006, Better rules or
stronger communities? On the social foundations of institutional change and its
economic effects Economic Geography, 82 (1). 1-25. ISSN 0013-0095
[20] Barca F., 2009, An Agenda for a reformed cohesion policy: A
place-based approach to meeting European Union challenges and expectations,
Independent Report, DG REGIO. 
[21] Rodriguez-Pose, A. and E. Garcilazo 2013, Quality of Government
and the Returns of Investment: Examining the Impact of Cohesion Expenditure in
European Regions, OECD Regional Development Working Papers, No. 2013/12,
OECD Publishing
Chapter 6: The evolution of Cohesion
Policy

1.     Introduction

Although the origins of Community policies
to tackle regional disparities can be traced back to the Treaty of Rome,
Cohesion Policy was only really initiated in 1989. In the years before, the Community
funds with territorial impact (i.e. the European Regional Development Fund
(ERDF), the European Social Fund (ESF) and the European Agriculture Guidance
and Guarantee Fund) financed predetermined national projects with little
European or subnational influence. In the 1980s, a series of events triggered a
policy change, most notably the Single European Act, the EU accession of Greece, Spain and Portugal and the adoption of the single market programme. This resulted in 1988 in
the first regulation integrating the Structural Funds under a common policy
umbrella to further economic and social cohesion. Key principles were
introduced at the same time, such as concentrating support on the poorest parts
of the EU, multi-annual programming, a strategic orientation of investment and
the involvement of regional and local partners. It also resulted in a
significant increase in funding for the period 1989-1993 compared to the past.
The Maastricht Treaty which entered into
force in 1993 established a new instrument, the Cohesion Fund. The Cohesion
Policy regulation adopted for the period 1994-1999, which also included the
Financial Instrument for Fisheries Guidance, incorporated the key principles of
concentration of resources, multi-annual programming and additionality of EU
funding. It also strengthened the rules on partnership and evaluation. The
financing allocated to Cohesion Policy was doubled and covered a third of the
EU budget.
The 2000-2006 period began with Member
States agreeing the ‘Lisbon Strategy’ (in March 2000) with its focus on growth,
employment and competitiveness which became the leitmotiv of many EU policies
and triggered a shift in Cohesion Policy towards more emphasis on innovation.
The period also saw the biggest ever enlargement of the EU, with 10 new Member
States joining in May 2004. These added 20% to the EU’s population but only 5%
to its GDP. The enlargement accordingly increased disparities in income and
employment across the EU since the average GDP per head in the new countries in
PPS terms was less than half the existing average and only 56% of their
population of working age were in employment as compared with 64% in the
existing Member States. 
With the accession of Bulgaria and Romania, the 2007-13 period brought the highest concentration ever of Cohesion Policy
funding on the poorest Member States and regions (81.5% of the total). In line
with the ‘Growth and Jobs’ agenda launched in 2005, a quarter of the financial
resources were earmarked for research and innovation and around 30% for
environmental infrastructure and measures to combat climate change. Other
important changes introduced to make Cohesion Policy more efficient and
sustainable included the promotion of financial engineering instruments and the
creation of technical assistance facilities to help Member States to prepare
major projects of high quality.
This chapter reviews the evolution of
Cohesion Policy from 1989 to 2013. The first section describes the changes in
the funding and the geography of the policy. The second section describes how
the goals of the policy have evolved over time and the economic arguments
underlying these goals. 

2.     As
the funding grew, the geography became simpler 
2.1.      Cohesion Policy expenditure
increased as a share of GNI 

Cohesion Policy absorbs a relatively small
share of EU Gross National Income (GNI), reaching a high of 0.36% in 2012.
Nevertheless, over the last two decades, Cohesion Policy has become the main
source of EU funding for the Unions political agenda. At the same time, the accession
of less developed Member States and widening regional disparities have
increased the challenges to be tackled.
Figure 1: Cohesion policy expenditure in the EU, 1976-2012
The balance between the three funds (ERDF, ESF
and Cohesion Fund) which finance Cohesion Policy depends primarily on the
investment needs of the less developed regions and Member States. In the 1970s
and early 1980s, before the Cohesion Fund was introduced, overall expenditure
was low and split more or less evenly between the ESF and ERDF. With the
accession of Greece, Spain and Portugal, their need for more infrastructure
investment led to an increase in the relative amount of funding allocated to
the ERDF. 
In the 1990s, the Cohesion Fund was introduced
to increase the support for investment in transport and environmental
infrastructure in countries with low GNI. Up to 2006, the amount involved was
only around 0.03% of EU GNI. Between 2007 and 2012, expenditure financed by the
Cohesion Fund doubled as a share of GNI as a result of the EU enlargements of
2004 and 2007 and the entry of 12 countries with very poor infrastructure
endowment. 

2.1.1.   Cohesion Policy in the 1990s

In the 1990s, Cohesion Policy expenditure
relative to EU GNI increased by 150% with much of the increase occurring in the
least developed Member States: from 1% to 2.3% of GNI in Portugal, from 1% to 1.8% of GNI in Ireland, from 0.6% to 1.7% in Greece and from 0.3% to 0.9% in Spain (see Figure 75). The remaining Member States received funding of between 0.05% and
0.2% of their GNI during the 1990s.
Figure 2: Cohesion Policy expenditure per MS, 1990-1999

2.1.2.   Cohesion Policy since 2000

Cohesion Policy expenditure between 2000 and
2006, remained relatively high in Portugal (1.8% of GNI), Greece (1.4%) and Spain (0.9%). In the 10 Member States which joined the Union in 2004, which had
only a limited time to carry out Cohesion Policy expenditure before the end of
the period, the amount varied between 0.2% of GNI and 0.6%, except for Cyprus (0.1% of GNI). 
Figure 3: Cohesion Policy expenditure per MS, 2000-2006
Cohesion Policy expenditure between 2007 and
2012 was higher in relation to GNI, in part because a large part of the funding
for the 2000-2006 period was spent in the three years 2007 to 2009 on top of
spending from the funding for 2007-2013. Exenditure in the three Baltic States
amounted on average to between 2.5% and 3% of their GNI a year over this
period, while in Hungary, it represented 2.3% of GNI and in Poland, 2.1%, more than in any of the Member States in the 2000-2006 period. 
In Portugal, expenditure under Cohesion Policy
increased slightly to 1.9% of GNI a yyear and in Greece, to 1.6%, while in Malta, Slovenia, Bulgaria, the Czech Republic and Slovakia, it amounted to between 1% and 1.5% of
GNI. 
The EU-15 with the exception of Portugal, Greece and   Spain received between 0.2% and 0.03% of their GNI a year.
Figure 4: Cohesion Policy expenditure per MS, 2007-2012

2.2.      The geography of the policy
became simpler between 1989 and 2013

From 1989, regions were categorised into
different groups in terms of policy objectives and the scale of funding
received. There have been three tendencies since then: (1) the maintenance of
continuity in the support provided, (2) a reduction in the categories of
regions and (3) a shift to a simpler geographical coverage. 
Continuity
There has been continuity in the way that
regions receiving the most support are defined. These were categorised as ‘Objective
1’ up to 2006, ‘Convergence’ up to 2013 and ‘less developed’ from 2014, but in
each case, they have been defined as those with GDP per head in PPS terms below
75% of the EU average. The regions in question, which have consistently been
defined in nearly all cases at the NUTS 2 level, are a mix of administrative
and purely statistical entities, which as such do not necessarily correspond
with functional labour markets, functional economic urban areas or political
jurisdictions. 
The population covered by the category
concerned has fluctuated over the five programming periods. In the first two
periods, 25% of EU population lived in Objective 1 regions. The enlargement in
2004 increased the proportion to 34%. Then convergence of GDP per head towards
the EU average of some of the regions covered reduced the proportion to 32% in
the 2007-13 period, despite the accession of Romania and Bulgaria and the extension of support to them. Continuing convergence has led to a further
reduction in the proportion to 25% for the 2014-2020 period, back to what it
was 25 years ago.
Table
1 Population by category of
region, 1989-2020 (%)
   || 1989-1993 || 1994-1999 || 2000-2006 || 2007-2013 || 2014-2020 
 Obj. 1 (1989-06)- Convergence (2007-13) - Less Developed (2014-20) || 25.4 || 24.6 || 34.1 || 31.7 || 25.4 
 Transition Regions ||   || 0.3 || 2.9 || 7.3 || 13.5 
 Objectives 2 (1989-06)-5b (1989-99) || 21.7 || 25.0 || 15.2 || 61.0 || 61.0 
 Objectives 3 (1989-06)-4 (1989-99) || 74.6 || 75.0 || 63.0 
 Regional Competitiveness and Employment (2007-13) - More developed (2014-20) ||   ||   ||   
 Objective 6 ||   || 0.4 ||   ||   ||   
 Cohesion Fund ||   || 16.9 || 30.9 || 34.3 || 25.8 
 Population of || EU-12 || EU-15 || EU-25 || EU-27 || EU-28 
 Objective || 1989-1993 || 1994-1999 || 2000-2006 || 2007-2013 || 2014-2020 
 1 || development and structural adjustment of regions where development is lagging behind; || Convergence || Less developed 
 Ex-1 || n/a || 1994-1996 Abruzzo || Phasing-out Objective 1 || Phasing-out and -in || Transition 
 5b || Promotion of rural development || Development and structural adjustment or rural areas * || Objective 2: supporting the economic and social conversion of areas facing structural difficulties; || Regional competitiveness and employment || More developed 
 2 || Converting the regions, frontier regions or parts of regions seriously affected by industrial decline || Converting the regions or parts of regions seriously affected by industrial decline 
 3 || Combating long-term unemployment || Combating long-term unemployment and facilitating occupational integration || Objective 3 Training systems and employment policies 
 4 || Occupational integration of young people || Adapting the workforce to industrial changes 
 6 || n/a || Development and structural adjustment of regions with an extremely low population density || Part of Objective 1 
 Number of categories ** || 5 || 7 || 4 || 3 || 3 
*    From 2000 onwards, part of the
support for rural development was financed by the second pillar of the Common
Agricultural Policy outside Cohesion Policy programmes
** Not including community initiatives
or subsequent the territorial cooperation objective. 
Reduction in categories of regions
The categories of region since 1989 have been
reduced from five in 1989-1993 and 7 in 1994-1999 to three in 2007-2013 and
2014-2020 (Table 23). In the 1989-1993 period, there were three categories
specifically aimed at reducing regional disparities: Objective 1 to assist less
developed regions, Objective 2 to support the economic conversion of areas
seriously affected by industrial decline and Objective 5b to help the
development of rural areas. The last two categories could overlap and typically
covered much smaller areas than NUTS 2 regions, identified as having the most
pressing problems. The other two categories covered the whole of the EU outside
Objective 1 regions: Objective 3 to provide support for combat long-term
unemployment and Objective 4 for the integration of young people into
employment. 
These categories remained in force in the
period 1994-1999 period, when EU enlargement in 1995 to include Austria, Sweden
and Finland led to the creation of a new category specifically to provide
support to the last two countries: Objective 6 to assist regions with an
extremely low density of population. In addition, the first Transition category
was created for Abruzzo to provide a measure of support in order to reduce the
economic effect of Objective 1 status and funding being withdrawn. 
In the 2000-2006 period, Objective 5b was
amalgamated into Objective 2, the aim of which was generalised to cover the
support for the economic and social conversion of areas, again typically much
smaller than NUTS 2 regions, facing the most pressing structural problems of
whatever kind. At the same time, the transition category was extended to
support the ‘phasing-out’ of regions that received Objective 1 funding in the
previous period but in which GDP per head had risen above the 75% threshold. Objective
3 and 4 were combined and continued to cover all the non-Objective 1 regions. 
In the 2007-2013 period, Objective 1 was
renamed ‘Convergence’ and Objective 2 and 3 were combined under the term ‘Regional
Competitiveness and Employment’. The Transition category was expanded to cover both
‘phasing-in’ and ‘phasing-out’ regions, the former being those in which GDP per
head had risen to more than 75% of the EU-15 average, the latter those where it
was still below 75% of the EU-15 average but above 75% of the new EU-27 average
resulting from the entry of the 12 central and eastern European countries. The
funding provided to these, while being much smaller than to Convergence
regions, was significantly larger than that available to Regional
Competitiveness and Employment regions.
For the present 2014-2020 period, three
categories remain but their names have been changed again to ‘Less developed’,
‘Transition’ and ‘More developed’. The Transition category now covers all
regions with GDP per head between 75% and 90% of the EU-27 average, though
regions which were Convergence ones in the previous period receive more funding
than the others.
A shift to a
simpler geographical coverage
The proportion of EU population in what are now
termed ‘less developed’ regions increased with the 2004 enlargement from 25% of
the EU-15 population to 34% of the EU-25 population. Despite the entry of
Romania and Bulgaria in 2007 and of Croatia in 2013, the convergence of GDP per
head towards the EU average in many of the regions led to the population in
those remaining with GDP per head below the 75% threshold falling to 32% of the
EU-27 total in 2007 and then to 25% of the EU-28 total in 2014.
Under Objective 2 (and Objective 5b up to
1999), the approach was, as noted above, to concentrate support on the areas
with the most pressing needs, which were often very small, sometimes even parts
of a municipality. Such 'micro-zoning' often made the design and implementation
of programmes difficult because to tackle the development problems concerned
effectively in many cases required investment in neighbouring areas and not
just in the small areas eligible for support. In 2007, ‘micro-zoning’ was,
therefore, dropped and the 'Regional Competitiveness and Employment' category
was created to cover all regions apart from the Convergence and Transition
ones. This continues to be the case in the 2014-2020 period, though the names
of the categories have been changed.
In the 1994-1999 period, the Cohesion Fund
covered Ireland, Spain, Portugal and Greece, which accounted for 17% of the
EU-15 population. In the next period, these four countries remained eligible,
though support was withdrawn from Ireland in 2003 as growth had raised its GNI
well above the 90% threshold. The 10 countries that joined the EU in 2004 also became
eligible for support, increasing the coverage to 31% of the EU-25 population.
In the 2007-2013 period, the entry of Romania and Bulgaria increased the
population covered to 34% of the EU-27 total, though support for Spain was phased out because of the increase in its GNI. In the 2014-2020 period, the Cohesion
Fund covers Greece, Portugal and all 13 countries that have joined the EU since
2004, which together account for 26% of the EU-28 population. 
 Box on Macro-regional cooperation Macro-regional strategies are a new way of supporting territorial cooperation, representing a joint response to common environmental, economic or security related challenges in a particular area. Though no additional EU funding is provided, help is given in directing Cohesion Policy programmes to the pursuit of shared goals. Two macro-regional strategies have been agreed so far, one for the Baltic Sea Region (adopted in 2009) covering the environment, economic development, accessibility and security, and the other for the Danube region (adopted in 2011) focused on connectivity, the environment, prosperity and capacity building. There are now over 100 flagship projects in the Baltic Sea Region and 150 projects are in the process of being implemented in the Danube Region out of 400 (involving expenditure of EUR 49 billion) which are being considered. The European Council has invited the Commission to present an EU Strategy for the Adriatic and the Ionian Region by the end of 2014. 
 Box on Territorial Cooperation programmes started in 1989 with INTERREG –   INTERREG I (1990-1993) The INTERREG Initiative was launched in 1990 in order to help tackle the disadvantages created by national administrative boundaries separating neighbouring regions in the emerging Single Market. It focussed purely on cross-border cooperation with an allocation of EUR 1.6 billion (at 2011 prices) or just over 2% of total Cohesion policy funding. It included 31 Operational Programmes in internal and external border regions and provided support to over 2,500 projects. –   INTERREG II (1994-1999) The INTERREG II Initiative, from 1994 to 1999, had a larger budget of EUR 4.9 billion (again at 2011 prices) and extended the scope of territorial co-operation. The number of cross-border programmes almost doubled from 31 to 59 as a result of the accession of Austria, Finland and Sweden in 1995 and the creation of a dedicated instrument for cooperation between regions either side of external borders. Programmes were also extended to cover support for education, health, media services and language training. In addition, a transnational strand was created to support cooperation across large contiguous areas and the exchange of information and sharing of experience in regions in the different countries concerned. –   INTERREG III (2000-2006) The 2000–2006 period saw a further enlargement of the EU and increase in border regions. The budget for INTERREG-III was increased to EUR 6.2 billion, with funding for transnational cooperation increased by EUR 890 million and that for interregional cooperation reduced (by EUR 150 million). –   Territorial Cooperation (2007-2013 and 2014-2020) In the 2007–2013 period, Territorial Cooperation was distinguished as an objective of Cohesion Policy and was allocated a budget of EUR 8.9 billion (including support for the Instrument for Pre-Accession, IPA, and European Neighbourhood Partnership Instrument, ENPI), or 2.5% of the total. For 2014-2020, the budget has been maintained in real terms despite a slight reduction in the overall budget for Cohesion Policy. Table 2: Funding for territorial cooperation, 1989-2020 (EUR billion at2011 constant prices) 
   || 1989-1993* || 1994-1999 || 2000-2006 || 2007-2013 || 2014-2020 
 Cross-border || 1.64 || 3.64 || 3.90 || 6.60 || 6.62 
 Transnational ||   || 0.71 || 1.60 || 1.80 || 1.82 
 Interregional ||   || 0.55 || 0.40 || 0.45 || 0.50 
 Total || 1.64 || 4.90 || 6.20 || 8.88 || 8.94 
 Share of Cohesion Policy Funding (%) || 2.2 || 2.1 || 1.9 || 2.5 || 2. 8 
 Source: Structural Fund reports, Ex-post evaluation of INTERREG and SFC ||   
 * Refers to 1990-1993 ||   ||   ||   ||   ||   

2.3.      Funding
remains concentrated on the less developed regions

From 1989 onwards, the EU Budget became a multi-annual
one. This facilitated the adoption of a long-term perspective for the
programmes funded under Cohesion Policy. The first period was five years
(1989-1993), the second six (1994-1999) and the third and subsequent periods
seven. The bulk of funding has consistently been
allocated to the less developed regions (Table 25). If the Cohesion Fund is
included, the share going to these regions has changed very little since 1989,
from 76% in 1989-1994[1]
to 73% in 2014-2020, though with a high of just over 80% in 2007-2013. 
Table 3: Funding distribution between categories
of regions, 1989-2020 (%)
   || 1989-1993 || 1994-1999 || 2000-2004 || 2004-2006 || 2007-2013 || 2014-2020 
 Less developed || 73.2 || 61.6 || 63.6 || 63.2 || 59.0 || 53.5 
 Transition || 0.0 || 0.2 || 2.6 || 2.0 || 7.5 || 10.8 
 More developed || 23.6 || 27.4 || 24.3 || 19.1 || 12.9 || 16.5 
 Cohesion Fund || 3.1 || 10.8 || 9.4 || 15.7 || 20.7 || 19.2 
 Less developed and Cohesion Fund || 76.4 || 72.4 || 73.1 || 78.9 || 79.7 || 72.8 
 Total || 100.0 || 100 || 100 || 100 || 100 || 100 
 EU || EU-12 || EU-15 || EU-15 || EU-25 || EU-27 || EU-28 
 Source: Structural Fund Reports, SFC and REGIO calculations. ||   ||   ||   

The aid intensity in less developed regions (funding relative to the population
covered) started out at EUR 110 per person (at 2011 constant prices), increased
to EUR 259 in the EU-15 in the 2000-2006 period, declined to EUR 188 in the 2007-2013
period and has been reduced further to EUR 180 per person for 2014-2020 
The Cohesion Fund had an aid intensity of EUR
54 per person (at 2011 prices) when it was first introduced in the 1994-1999
period. With enlargement in 2004, it fell to just below EUR 50, though it was
increased to EUR 60 in the 2007-2013 and to EUR 62 per person for 2014-2020. 
The aid intensity in Transition regions started
at the relatively low level of EUR 49 per person in 1994-1999 (when only
Abruzzo was covered) and was increased to EUR 101 in the 2007-2013 period, but
it has been reduced to EUR 66 per person for the 2014-2020 period.
Aid intensity in the more developed regions for
2014-2020 as in the previous period is slightly over EUR 20 per person, compared
to around EUR 30 in the 1994-1999 and 2000-2006 periods[2].
Table 4: Annual Aid intensity per category of
region, EUR per head (at 2011 constant prices), 1989-2020
   || 1989-1993 || 1994-1999 || 2000-2004 || 2004-2006 || 2007-2013 || 2014-2020 
 Less developed * || 110 || 210 || 259 || 179 || 188 || 180 
 Transition ||   || 49 || 67 || 67 || 101 || 66 
 More developed || 13 || 32 || 29 || 29 || 21 || 22 
 Cohesion Fund *** || 36 || 54 || 48 || 49 || 60 || 62 
 Total ** || 42 || 86 || 89 || 83 || 100 || 84 
 EU || EU-12 || EU-15 || EU-15 || EU-25 || EU-27 || EU-28 
 Source: Structural Fund Reports, SFC and REGIO calculations. Annual deflator of 2% ||   
 * ERDF+ESF, ** ERDF+ESF+CF, *** In the period 2007-2013, Spain received phasing-out support. The aid intensity excluding Spain was 76. 
 Box: Allocations and payments In this report, Cohesion Policy funding is measured in two ways: ·   by allocations ·   by expenditure or payments Allocations are the amounts of financial support from the ERDF, ESF and Cohesion Fund that are allocated to Operational Programmes. Here, they have been transformed into 2011 constant prices using a standard deflator of 2% a year and are expressed in terms of annual aid intensities by relating the amounts to population in each programming period from 1989 onwards in the different countries and by category of region. Expenditure relates to the payments made by the Commission to the Member States from the ERDF, ESF and Cohesion Fund to reimburse for spending on co-financed projects. The figures are then expressed in relation to GNI. These two data sources are difficult to compare. Allocations precede the actual expenditure carried out on projects. Payments are only made after eligible expenditure has been declared to the Commission and assessed as being reimbursable. Allocations are in fixed prices while payments are in current prices. In addition, not all allocations are necessarily spent in the time allowed – within two years of the period formally ending. Some allocations might be rolled over into the next period, others withdrawn if Member States are unable to comply with the rules governing expenditure. 

2.4.      The European Structural
Investment Funds and Cohesion Policy

The funding
allocation to the five ESI funds has grown since 1989-1993 period as the EU expanded
and the challenges facing the ESI funds intensified from EUR 75 billion to EUR
460 billion in the 2007-2013 period. 
The total for the
2014-2020 period is lower at EUR 400 billion. The total and the distribution
between the funds may still change as MS can shift funding from the first
pillar of CAP to EAFRD (or vice versa) and from ERDF to ESF or depending on
their investment needs and priorities. 
The way this
funding is coordinated has evolved over time. Until the 2000-2006 period,
funding from EAFRD and EMFF was often combined with ERDF and ESF funding in
single programmes. In the 2007-2013 period, EAFRD and EMFF funded separate
programmes to stimulate rural development and the development of areas
dependent on fisheries. 
In the new
programming period, the European Structural Investment Funds have once again
been included under the same umbrella. The partnership agreements cover all ESI
funds and the common rules facilitate a more coordinated implementation.
Table 5 Allocation per fund (EUR billion, at 2011
prices), 1989-2020 
   || ESF || ERDF || CF || EAFRD || EMFF || Total 
 1989-1993 || 24 || 39 || 2.2 || 10 ||   || 75 
 1994-1999 || 67 || 119 || 20 || 35 || 4.1 || 245 
 2000-2006 || 79 || 150 || 32 || 45 || 4.6 || 311 
 2007-2013 || 78 || 205 || 71 || 102 || 4.4 || 460 
 2014-2020 || 71 || 181 || 56 || 85 || 6.6 || 400 
Note that the funds are identified using their current
name and that the EAFRD and EMFF had a different name in earlier periods.
Cohesion Fund was only launched in 1992 and in operation in 1993.

2.4.1.   The Common Agricultural Policy
(CAP) and rural development

The first
generation of rural development activities under the Common Agricultural Policy
(CAP) was introduced in the 1970s in the form of measures to support structural
change in agriculture and to help maintain farming in areas affected by natural
constraints. Other measures followed, including support for  young farmers setting
up and investment in processing and marketing of agricultural products.
At the beginning of
the 1990s, the policy was extended to non-agricultural, territorially oriented,
activities, which were clearly linked to the economic and social development of
rural areas and enabled farmers to diversify into other activities. The
introduction of support for LEADER, a ‘bottom-up’ approach to implementing
local development strategies, was supplemented by measures help maintain the cultural
and natural heritage and to improve local infrastructure and basic services in
rural areas.
Under the Agenda 2000 reform, rural development
policy was established as the second pillar of the CAP with the aim of contributing to the economic, social and cultural development of
rural areas in the EU. 
For the period 2007-2013, a more strategic
approach was introduced in respect of rural development programmes. The budget
for rural development totalled EUR 96.3 billion including amounts resulting from
transfers from pillar I of the CAP to rural development (under the ‘modulation
system).
Although cohesion is not an explicit
policy goal of the CAP, it is intended to take account of 'the particular
nature of agricultural activity, which results from the social structure of
agriculture and from structural and natural disparities between the various
agricultural regions[3].
Its aim is to ensure economic and social progress in agriculture and rural
areas while providing support for the supply of reasonably-priced food to EU
consumers.
In addition, the
regulation governing the Agricultural Fund for Rural Development (EAFRD) links
rural development to economic and social cohesion, specifying that the EAFRD shall
contribute to the Europe 2020 Strategy by promoting sustainable rural
development throughout the EU in a manner that complements the other
instruments of the CAP, Cohesion Policy and the Common Fisheries Policy. [4] 
Economic cohesion
At EU level, the
combined primary sectors - agriculture, forestry and fishing –and food
represent a sizable part of the EU economy accounting for employment of 16.5
million people (7.3% of the total) and 3.7% of gross value-added (GVA) in 2011
. These figures mask significant variations across countries as the agri-food
sector is more important in the EU-12, particularly in respect of employment, ,
and in rural areas.
The CAP
contributes to economic cohesion through its two pillars. Direct payments help
to underpin the viability of farming across the EU, and the communities which
depend on it, by providing a reliable source of income for producers and making
them less vulnerable to fluctuations in prices. In 2011,
expenditure on the first pillar of the CAP amounted to EUR 44.0 billion[5], by far the biggest
proportion going on direct aids to farmers of: EUR 40.2 billion[6]. Expenditure on rural
development, on the other hand, is intended to support the economic viability of
rural areas through financing investment, the transfer of know-how, and
measures fostering innovation.
Social Cohesion
The CAP also contributes to furthering social
cohesion, mainly through support for rural development. Around a third of all those
at risk of poverty in the EU live in thinly populated (rural) areas, so e rural
development policy is important for social inclusion. In addition to measures
supporting employment both in agriculture and other sectors, support is also
provided to assist the development of basic services and infrastructure. Consequently,
by the end of 2012, some 127 600 young farmers had received support to start up
new activities and some 34 000 villages had been renovated.
The support can also
be used by Member States to help integrate disadvantaged groups, such as Roma
by assisting the setting-up and development of non-agricultural businesses, job
creation, investment in small scale infrastructure and local basic services,
including through LEADER local development strategies.
Territorial cohesion
In addition to
its rural development ‘pillar’, the CAP has a strong territorial dimension
under its first pillar through the support it gives to farmers who perform an
important land management function and through the fact that agriculture,
forestry and the agri-food sector still make a significant contribution to the
socio-economic development of rural areas. As regards the rural development
pillar, the policy includes economic, social and environmental dimensions based
on a territorial approach and can help to maintain a sustainable balance
between urban and rural areas.
Just over 32% of EU support for rural development was allocated
to Convergence regions in the 2007-2013 period and by June 2013, Over EUR 35.3
billion of the EAFRD had been spent in these, almost EUR 15.2 billion on
measures to improve the environment and countryside, nearly EUR 12.9 billion on
improving the competitiveness of agriculture and forestry, EUR 5.1 billion on improving
the quality of life in rural areas and encouraging diversification of the rural
economy and almost EUR 1.2 billion on LEADER.
The new CAP reform and its contribution to cohesion
The CAP continues to be divided into two
pillars in the 2014-2020. The total budget amounts to EUR 252 billion for direct
payments (pillar I) and EUR 95 billion for rural development (pillar II). The
direct payment system includes new elements that are intended to increase the
contribution of CAP to Cohesion Policy, such as through a more balanced,
transparent and fairer distribution of direct payments between farmers  and between 
countries. Direct payments will, moreover, be more targeted, by, for example,
providing an additional payment to all EU young farmers and potentially to
specific regions with natural constraints.
An important change, which is directly linked to
EU cohesion objectives concerns the new rural development framework, in which rural
development policy is partly harmonised and coordinated with other ESI funds with
the aim of improving the chances of achieving the Europe 2020 objectives..
In the new programming period, Member States
are formulating their rural development strategies on the basis of 6
priorities, one of which, in line with cohesion objectives, is the 'promotion
of social inclusion, poverty reduction and economic development of rural areas'.
In addition, innovation, safeguarding the environment and adapting to climate
change are cross-cutting objectives which all programmes are pursuing. 
This stronger strategic focus should enable policy
to be better targeted on areas and groups of people in need, so improving its
effect on cohesion.

2.4.2.   The Common Fisheries Policy and Integrated Maritime Policy

The European Maritime Fisheries Fund (EMFF) aims
to ensure that fishing is carried out in a sustainable
and efficient way and that the fisheries and aquaculture industry is both
economically viable and competitive, providing a decent standard of living for
those who depend on it. The fund was set up in 1994 and was initially called
the Financial Instrument for Fisheries Guidance (FIFG), becoming the European
Fisheries Fund in 2007. 
The European Maritime and Fisheries Fund (EMFF)
provide financial support for the implementation of the Common Fisheries
Policy. The first three pillars of the Fund focus mainly on helping the EU
fishing fleet and related sectors, such as aquaculture, inland fishing and the
processing of the products produced, to adapt to change. 
The fourth pillar of the EFF provides support for
the development of coastal areas dependent on fisheries in order to ensure
their long-term economic viability. Accordingly, the EMFF helps to tackle the
socio-economic disparities of coastal communities with a high dependence on
fisheries, which have gradually declined in recent years because of over-fishing
and increased global competition. 
In the 2007-2013 period the fourth pillar
provided EUR 0.6 billion support to the development of coastal areas dependent
on fisheries so as to ensure their long-term viability. In 2010, there were 93
coastal NUTS-3 regions where employment in fishing accounted for over 5% of
jobs and 25 regions where the gross value-added generated by fishing accounted
for over 10% of the total. The extent of dependency is declining in terms of
both jobs and value-added as fishing is displaced by others activities. The EFF
provides support to projects that add value to fisheries and aquaculture
products, create or maintain jobs, encourage entrepreneurship and innovation
and improve the quality of the coastal environment. 
In the 2007-2013 period, Convergence regions
received around 75% of the EUR 4.4 billion funding, allocated on the basis of
the historical share of support for fisheries in cohesion policy. For other
regions, the allocation took account of sector-specific criteria, such as
employment in the sector and the structural adjustment needed. 
The 2014-2020 period relies exclusively on
sector-specific criteria for distributing the budget with the aim of ensuring a
more balanced distribution of funding and avoid absorption problems in
Convergence regions where fisheries are less important.
One important feature of the ESI Funds that is
likely to play an important role in coastal communities is Community-led Local
Development, which will allow local communities to combine the funds for
supporting fisheries-oriented action with broader strategies to diversify the
economies of areas still dependent on fishing. 
The Integrated Maritime Policy, launched in
2012, is aimed at providing a more coherent approach to maritime issues. It
calls for increased coordination between different policy areas while
safeguarding biodiversity and protecting the marine environment. A central
theme is economic growth based on various maritime sectors, including blue
energy (such as off-shore wind power), aquaculture, maritime, coastal and
cruise-ship tourism, marine mineral resources and blue biotechnology, sectors
which are interdependent and rely on common skills and shared infrastructure
such as ports and electricity distribution networks. The Policy also covers
horizontal measures such as maritime spatial planning, integrated surveillance
and marine know-how which can improve the management of oceans. In March 2013,
the Commission proposed legislation to create a
common framework for maritime spatial planning. Once in place, this
can provide businesses with the legal certainty they need to invest.
 The European Globalisation Adjustment Fund (EGF) The European Globalisation Adjustment Fund was set up in 2006 to provide support to workers losing lost their jobs because of globalisation. More recently, it has been extended to workers made redundant as a result of the crisis. Workers are eligible for support when a large company closes down, a sector is affected by trade developments or production is moved abroad. The EGF cannot be used to keep companies in business or to help them modernise or restructure. In general, EGF support can be requested only when more than 1,000 workers are made redundant by a single company or in a particular sector concentrated in a region or in a few neighbouring regions. Between 2007 and 2013, 128 requests for support from the EGF were received and almost EUR 0.5 billion was paid out to help close to 100,000 workers. The projects supported consist mainly of those aimed at helping workers to find a new job or set up in business for themselves, by providing career advice, mentoring and coaching, training, mobility and relocation allowances and business advice. For the 2014-2020 period, the EGF has a maximum budget of €150 million a year, double that of the previous period, and a co-financing rate of up to 60%. The self-employed and workers on fixed-term contracts made redundant are also eligible for support. In addition, between 2014 and 2017, in regions with high youth unemployment, the young unemployed can receive support in equal numbers to workers being assisted by the ESG in the normal way. 

2.5.    Aid intensities in less developed
regions rose up to 2000-2006 and have since declined

Aid intensities in less developed regions in
the different Member States mirror the trend at EU level. Between 1989 and
2006, they increased in all Member States (see Figure 78, where the size of
bubbles shows the share of national population in less developed regions). Belgium and the Netherlands each had one less developed region in 1994-1999, which became Transition
regions in 2000-2006. In France and UK, the proportion of population in less
developed regions was very small throughout the period. In Greece, Portugal and  Ireland, all the population lived in less developed region in the 1989-1993
period, but by 2000-2006, the proportion in Ireland had fallen to 27% and in Portugal to 66%, though in Greece, it remained at 100%. 
Aid intensity was highest over this period in
the least developed among the regions covered. In 2000-2006, it averaged
between EUR 380 and EUR 490 a year in Convergence regions in Ireland, Portugal and Greece, but it was below EUR 150 a year in Austria and Finland.
Figure 5: Aid intensity in less developed regions
by Member State, 1989-2006
Source: Annexes of
1st Annual report on the implementation of the reform of the structural funds
for the period 1989-1993; Financial Annexes (volume II) of 11th Annual Report
of the Structural Funds (1999), DG BUDG, SFC and DG REGIO calculations
Note Aid
intensities include ESF, ERDF and Cohesion Fund. Cohesion Fund aid intensity
was assumed to be the same in all regions of a Member State receiving support.
Average aid intensities in less developed
regions at the EU level are lower in the 2007-2013 and 2014-2020 periods than
previously (around EUR 230 a year compared with EUR 284 in the EU-15 in the
2000-2006 period).
The aid intensities in less developed
regions in the EU-27 show the influence of limiting, or capping, funding
allocations to a fixed share of GDP which varies between countries, in part
according to their level of development but also taking account of other
factors. Capping was first introduced in the 2000-2006 period and remains in
force. The purpose is to avoid financial support leading to overheating of the
recipient economy as well as to ensure that Member States can absorb the
resources concerned and allocate them effectively to sufficiently mature
projects. 
As a result, aid intensities are no longer
highest in the least developed regions (see Figure 79). They are lowest, for
example, in Bulgaria and Romania as well as the UK. Aid intensities might
increase as a country develops and becomes more able to use funding effectively
(as in Slovakia or Poland) but decline after development reaches a certain
point (as in the Czech Republic). 
In Slovenia, Poland and Romania, the
capital city region is no longer in the less developed category in the
2014-2020 period, while in Slovakia, the Czech Republic, Hungary and Portugal,
it was not in this category in 2007-2013 as well. 
Figure 6: Aid intensity in less developed regions
by Member State, 2007-2013 and 2014-2020
Source: Annexes of
1st Annual report on the implementation of the reform of the structural funds
for the period 1989-1993; Financial Annexes (volume II) of 11th Annual Report
of the Structural Funds (1999), DG BUDG, SFC and DG REGIO calculations
Note Aid
intensities include ESF, ERDF and Cohesion Fund. Cohesion Fund aid intensity
was assumed to be the same in all regions of a Member State receiving support.
 Box on Outermost regions There are 8 ‘outermost’ regions in the EU, which are all located a long way from the respective countries to which they belong in the Atlantic Ocean, the Caribbean, the Indian Ocean and South America. Altogether around 4.6 million people live in these regions. Their specific situation was first recognised in a declaration attached to the Maastricht treaty in 1992 and subsequently in an article in the Amsterdam and Lisbon Treaties. All the regions have relatively high population growth, reinforced, in most of them, by net inward migration. Except for Madeira, all of them to have a level of GDP per head below the EU average, Mayotte (situated between Madagascar and the African coast with a population of around 213,000), which joined the outermost regions on 1 January 2014, having the lowest level at around a quarter of the EU average. Unemployment in all of them is significantly higher than in the rest of the EU, Canarias and Rèunion having the highest rates at 33% and 28%, respectively, in 2012, Madeira and Açores having the lowest rates, at 15% and 17%, respectively. In the 2014-2020 period, 6 of the 8 have been designated as ‘less developed’ regions for funding purposes, while Canarias is in the Transition category and Madeira in the more developed one. The average aid intensity for the regions in 2014-2020 is much the same as in 2007-2013 at a little over EUR 190 per person a year (at 2011 constant prices). The level in Madeira and Açores, however, has been reduced significantly because of their higher levels of GDP per head. It has also been reduced in two of the 5 French regions (Réunion and Guadeloupe), while it has risen in Guyane and Martinique. In Canarias, it has been increased substantially from a relatively low level to one similar to that in Mayotte, the fifth French region. Figure 7: Aid intensities in the outermost regions, 2007-2020 

3.     How
have the goals changed over time?

The ambition to reduce the development gaps
between regions dates back to the foundation of the European Economic Community
in 1957 with the Treaty of Rome, which states: "the Community shall aim
at reducing the disparities between the levels of development of the various
regions". This goal is still at the heart of Cohesion Policy. However,
the Union of today is radically different than the one of 57 years ago. The
various waves of enlargement have introduced new issues and new challenges as
well as increasing the scale of some of the initial ones. The interpretation of
the goal has also changed and is still evolving. 

3.1.      The initial focus was on
training and mobility

In the 1960s, the European Social Fund (ESF)
tackled regional development gaps by providing support for the geographical and
occupational mobility of workers. It helped workers in sectors that were
modernising or restructuring by providing them with short-term retraining allowances
and helped people, particularly those out of work, to relocate and seek jobs
elsewhere through resettlement grants. In the 1960s, however, unemployment
rates were low (see Figure 81) and most people who became unemployed quickly
found a new job. 
Figure 8: Unemployment rate, EU-6 EU-27, 1960-2012

3.2.      The 1970s and 1980s saw
structural unemployment and rapid changes in agriculture and manufacturing

In the first part of the 1970s, there was a
growing concern about job availability and the economic prospects of less
developed regions. While unemployment averaged less than 3% in the EU during
the 1960s, it increased from the mid-1970s on to reach 10% in the mid-1980s
with over 30 NUTS-3 regions having rates above 20%. This was a reflection of a
steep decline of employment in agriculture and manufacturing in many regions.
As a result, the policy focus shifted to supporting regions with a large
agricultural sector, those experiencing industrial decline and/or those with high
structural unemployment. A high level of youth unemployment led to measures
being targeted in particular on young people. 

3.3.      The countries joining the EU in
the 1980s and 2000s lacked key infrastructure 

The successive waves of EU enlargement have
altered the challenges for Cohesion Policy to tackle. While some of the
acceding countries were highly developed and very similar to existing Member
States, others were much less so in territorial as well economic and social
terms. 
In 1973, the UK and Denmark had levels of
economic development similar to the six original Member States (see Figure 82).
In UK, GDP per head in PPS terms was 93% of the then EU average, in Denmark it was 7% above the average. Unemployment was also lower than the average in both
cases. Ireland, on the other hand, was much less developed with a GDP per head
of only 60% of the EU-6 average and an unemployment rate twice the average. 
When Greece joined in 1981, it had a GDP per
head of 85% of the EU average and a lower unemployment rate. Portugal and Spain were both considerably less developed than the existing Member States when they
joined in 1986, GDP per head in the first being only 50% of the EU average and
in the second, 69%. Spain too had an unemployment rate of 17%, almost twice the
EU average at the time. In all three countries, infrastructure was either
lacking or of poor quality. 
The 1995, Sweden and Austria both had above
average levels of GDP per head and below average unemployment, while in
Finland, GDP per head was not far below the EU average (90%) but the
unemployment rate was 15%, well above the EU average at the time (10%). Though
the enlargement did not pose new challenges for Cohesion policy, it did
increase the territorial diversity of the EU adding more mountainous areas and
sparsely populated areas in the far north. 
The 2004 enlargement posed a far greater
challenge in that the 10 new Member States had a GDP per head of between 40%
and 76% of the EU average. Five of them had unemployment rates above the EU
average – in the case of Poland and Slovakia, double the average. The standard
of infrastructure in all the countries was also far lower than in most of the
existing Member States (see Chapter 2).
When Romania and Bulgaria joined in 2007, they
were the least developed countries to enter the Union, with GDP per head of
less than 40% of the EU average and infrastructure of a far lower standard than
in the rest of the EU.
In 2013, Croatia joined the EU with a GDP per
head of 61% of the EU average and an unemployment rate of 16%, substantially
higher than the average of 10%.
Figure 9: GDP per head per enlargement, 1975-2013
Figure 10: Unemployment per EU enlargement, 1973-2013

3.4.      Improving transport and
environmental infrastructure

With the creation of the Cohesion Fund in 1992,
improving transport and environmental infrastructure became explicit goals of
Cohesion Policy. 
The Cohesion Fund was set up as an accompanying
measure to the establishment of the Single Market. It was intended to ensure
that all Member States, including those which were on the periphery of the EU and
were lagging behind in terms of economic development, were able to share in the
growth stemming from the removal of barriers to competition in the markets
concerned. Moreover, as the Maastricht criteria limited public debt and public
deficits, it was harder than before for countries with poor infrastructure
endowment gap to catch up with the rest of the EU.
The support provided was, therefore, aimed at helping
the countries to do this by contributing to the cost of extending and improving
their transport networks and environmental infrastructure and so remove
obstacles to their economic and social development. At the same time, the investment
concerned was also designed to further the Single Market project – and
ultimately Economic and Monetary Union – by improving transport links with the
rest of the EU and ensuring a minimum standard of infrastructure across the EU.
Unlike the ERDF, the focus from the start was
on the situation at national rather than at regional level and on the gap
between the lower income countries and the rest of the EU rather than on
disparities between regions. Accordingly, eligibility for receipt of Cohesion
Fund support was couched in national terms – having a Gross National Income
(GNI) per head of less than 90% of the EU average. 
In practice, the Cohesion Fund has helped lower
income countries to comply with environmental Directives relating to clean
drinking water, urban wastewater and solid waste disposal. The goal of facilitating
compliance with EU environmental Directives in Member States with a GNI below
90% extends beyond the goal of reducing regional disparities in development and
is, accordingly, an additional objective of Cohesion policy.
The concentration of support on transport and
environmental infrastructure has remained since the creation of the Cohesion
Fund. The characteristics of the countries receiving support, however, have
changed markedly as indicated above in terms of both the level of economic
development and need for infrastructure.

3.5.      The Lisbon and Gothenburg Agenda

The Lisbon Strategy, adopted in 2000, was aimed
at boosting the competitiveness and knowledge-intensity of the EU economy by
among other thing increasing investment in innovation. The strategy was
re-launched in 2005 with a stronger focus on growth and jobs and the
introduction of national reform programmes to ensure greater coherence and greater
ownership of the strategy.
The Gothenburg Strategy adopted in 2001
focussed on sustainable development, i.e. meeting the needs of the present
without compromising the ability of future generations to meet their own needs.
This was followed by a more comprehensive Sustainable Development Strategy for
an enlarged EU in 2006.
The link between Cohesion Policy and the Lisbon and Sustainable Development Strategies was strengthened for the 2007-2013
programming period. New ‘earmarking’ requirements ensured that a large part of
Cohesion Policy funding went to support projects that contributed to the two strategies,
marking a further shift towards aligning Cohesion Policy with the overall policy
agenda of the EU.
The primary goal of reducing economic
disparities, however, remained intact in the process. The bulk of funding
continued to go to less developed regions (see above) and the earmarking
requirements were less stringent for these than for more developed regions. 

3.6.      Europe 2020, poverty reduction, climate change mitigation and beyond GDP

Compared to the Lisbon agenda, Europe 2020
added to two new elements to the political agenda of the EU, poverty reduction
(see Chapter 3) and a stronger emphasis on sustainability (see Chapter 4). This
has led to a change in the goals of Cohesion Policy (see Chapter 8) and to the
way policy is implemented, with a greater stress on action aimed at achieving
multiple goals.
This strategy has five headline targets set at
the EU and the national level, yet these issues also differ within Member
States. Each of these headline targets follows a different logic spatial logic.

In some case, the spatial concentration makes
matters worse. For example, the concentration of poverty and social exclusion
in small areas has strong negative externalities. In other cases, the spatial
concentration can be positive, in the case of innovation, or neutral, in the
case of GHG emissions or renewable energy. In the case of education the impact
of spatial concentration is mixed. A high concentration of early school leavers
is likely to generate negative externalities, but a concentration of tertiary
educated generates positive externalities. The latter is also impossible to
avoid as many tertiary educated will move to large cities in search of more
interesting job opportunities. 
The consequences of the spatial concentration
of high (or low) employment rates are ambiguous. The clustering of high
employment rates may lead to labour and skill shortages which can only be
resolved through people moving long distances. The clustering of low employment
rates is likely to depress wages and have negative externalities. Yet the inevitable
differences in size and economic structure of labour market areas and in labour
market regulations mean that identical employment rates are unrealistic. In
short, both large disparities in regional employment rates and zero disparities
are likely to produce negative externalities. The optimal situation is to have
limited employment rate disparities avoiding both depressed and overheated
labour market areas.
The way public policies can tackle these issues
also changes from one area to another. Reducing poverty requires a different
approach in areas with a high poverty rate than in one with an average rate.
Reducing greenhouse gas emissions efficiently needs different policies in urban
areas than in rural ones. Policies to boost innovation or enhance education
should take into account the current and the potential economic specialisation
of the region or city.
The differences between the EU targets and the
national targets reflect both a sense of realism, an understanding of the
externalities of concentration and likely future developments. 
For example, the 2020 index based on the
distance to the EU targets for smart and inclusive growth (Map 80) and the 2020
index based on the national targets[7]
(Map 81) show that overall, the distance to EU targets varies more with wide distances
for the less developed Member States. The average distance to the EU target is,
therefore, relatively wider for Greece, Romania, Bulgaria, Hungary, Croatia, Poland and Italy. 
The distance to national targets tends to be a little
smaller as Member States have opted to aim for a lower and more realistic
target for R&D expenditure if their starting level is low, which is the
case in most less developed countries. This suggests both a sense of realism
and that spatial concentration of R&D can be beneficial.
For the employment, education and poverty or
social exclusion national targets, however, Member States with the lowest rates
have often opted for ambitious targets, which implies that a substantial effort
is needed to achieve them. This shows that lagging Member States are eager to
catch up with the rest of the EU and recognise the potential negative
externalities of the spatial concentration of low employment rates, low
educational attainment levels and high rates of poverty or social exclusion.
The national targets for GHG emissions in the
effort-sharing mechanism involve a reduction for the more developed Member
States which have far higher emission levels per head than less developed
Member States which are allowed a moderate increase. This is a fairer
distribution of effort than specifying equal cutbacks which recognises that it
does not matter where GHG emissions occur.
 Map 2 Europe 2020 index, 2011 distance to EU targets || Map 3 Europe 2020 index, 2011 distance to national targets 
 Box on Committee of the Regions and the territorial dimension of Europe 2020 and other EU policies According to the Committee of the Regions (CoR), a ‘territorial dimension’ should be included in the design and implementation of the Europe 2020 strategy. The targets should, at least partly, be defined at regional level and progress indicators should be established to enable regions to monitor their progress in achieving them. In the Committee’s view, giving regions and local authorities a stronger role in the conduct of Cohesion Policy and in implementing Europe 2020 would increase ownership and help to make public investment more effective, though it is recognised that to achieve this also requires a further improvement in their administrative capacity. The CoR also pleads for strengthening the long-term regional investment focus and making it more crisis-resistant. The Committee’s view is based on a series of ‘works’[8] including a survey among Regional and Local authorities (LRAs), which found strong support for the Europe 2020 strategy among the 1000-plus respondents but in which many pointed to the lack of a strong territorial dimension in the strategy and of a clear role for LRAs. The LRAs indicated that they wanted to be more involved in all stages of the policy process and for cross-border interdependencies to be taken into account. A large majority of LRAs responding stated that the targets should be regionally differentiated, but there was s no consensus on how this should be done. Three alternative ways were suggested - that targets should be the same as the national ones, higher for more advanced regions or higher for lagging ones. The CoR pleads on this basis for a mixed approach combining both national and regional target setting differentiated by indicator and by country. Following the Commission’s guidance on how territorial impact should be assessed, the Committee has adopted a Territorial Impact Assessment strategy, which aims to take account of the territorial impact of EU policies on LRAs and to increase the visibility of territorial impact assessment in the pre-legislative and the legislative process. 

3.7.      Beyond GDP: poverty, human
development and well-being

The Treaty expresses the aim of reducing
regional disparities in development but does not define, except in very broad
terms, what kinds of disparity are being referred to. For many years, the focus
was primarily on reducing disparities in GDP per head and unemployment rates.
Over time, however, attention was extended to other aspects of development,
such as environmental quality, sustainability, poverty and social exclusion.
This can be seen as part of a more general move
towards better defining the way that development should be measured. The
Stiglitz, Sen and Fitoussi report on the measurement of economic performance
and social progress (2009) provides an excellent summary of what we know and
what needs to happen next. It emphasises that indicators should not be confined
to averages but cover their distribution across the population. For example,
growth of average income can in some cases be a result of increases for a
minority of the population and the majority might even experience a reduction.
This can, therefore, give rise to a disconnect between what official statistics
show and what most people experience, which tends to undermine their trust in
the indicators concerned. 
In parallel with the Stiglitz, Sen and Fitoussi
report, the European Commission published the ‘GDP and beyond’ communication
(EC 2009) in the same year. This identified five key ways of improving the
measurement of progress, including complementing GDP with environmental and
social indicators and the better reporting of distributional and inequality
aspects. 
In line with line, there has been a growing
demand that Cohesion Policy should 'also move beyond GDP' (EC 2008). Already in
the 2007-2013 period, many different measures of progress were taken into
account in deciding the most appropriate priorities and the strategies for
pursuing them (see EC 2010). For the 2014-2020 period, the European Commission
has requested the World Bank and ESPON to produce detailed maps to identify the
high-poverty areas on which policy should be targeted. 
Nevertheless, the categorisation of regions and
the Cohesion Policy funding they are eligible for in the period 2014-2020 were
still based primarily on GDP. A prerequisite for considering other indicators
which could be used to do this is a time series of reliable official statistics
at regional level. This is one of the reasons for the Commission investing in
better regional indicators of poverty and social exclusion as part of the EU
Statistics on Income and Living Conditions (EU-SILC). The combination of a
better territorial understanding of the EU (through regional and local
typologies) and better measurement of income distribution, inequalities and
poverty can provide an appropriate framework for Cohesion Policy to take
explicit account of these aspects (see EC 2013).

3.8.      What are the goals of Cohesion
Policy?

The above overview of how the goals of Cohesion
Policy have evolved over time can be summarised as follows. The reduction of
regional disparities in development is and remains a central goal and most of
the funding has consistently gone, and continues to go, to the least developed
regions. The nature of regional disparities being tackled, however, has changed
over the years. The initial focus on unemployment, industrial reconversion and
the modernisation of agriculture has broadened to include disparities in
innovation, education levels, environmental quality and poverty, as reflected
in the division of funding between policy areas. The process of reinterpreting
development disparities is ongoing and may lead in future to a stronger focus
on disparities in overall well-being.
In addition to the goal of reducing regional
disparities, Cohesion Policy has become more closely aligned with the overall
policy agenda of the EU. In the 1990s, Cohesion Policy funding began to be used
as well to improve the trans-European Transport Network in support of the
Single Market and to improve and extend environmental infrastructure to help
Member States to comply with EU environmental Directives. Although investment
in transport infrastructure might have contributed to a reduction in economic
disparities, investment in environmental infrastructure had little impact on
the economic development of the regions concerned. Accordingly, improving
environmental infrastructure can be seen as an additional goal of Cohesion
Policy. The adoption of the Lisbon and Gothenburg strategies led to a stronger
emphasis on innovation and sustainability and Europe 2020 has resulted in the
goals of Cohesion Policy being extended to reducing poverty and social
exclusion. The closer alignment of the policy to EU objectives has also
influenced the way in which goals are pursued. For example, the measures
adopted to boost smart growth have to take account of their impact on
sustainability and inclusion. 
The pursuit of EU-wide objectives is to a large
extent compatible with reducing regional disparities, in the sense that, for
example, supporting innovation or the sustainability of development in weaker
regions is an important means of achieving this end. 
The closer link to the overall EU political
agenda also underlines the fact that Cohesion Policy is not exclusively
focussed on the less developed regions but it supports investment in all
regions which is aimed at furthering common EU objectives.
 Box on Territorial Cohesion and the Lisbon Treaty of 2007 With the Lisbon Treaty in 2009, territorial cohesion was explicitly added to the goals of economic and social cohesion, though it was already an implicit objective of policy. Concluding the debate launched by the Green paper on territorial cohesion, the Fifth Cohesion Report summarised the changes introduced by the increased emphasis on territorial cohesion as reinforcing (1) the importance of access to services, (2) sustainable development, (3) functional geographies and (4) territorial analysis. Since 2010, the European Commission has taken action to address all four of these issues. (1)       Access to services Both Europe 2020 and the Budget for 2014-2020 include specific action to improve digital and physical access to services. The Digital Agenda for Europe is aimed at ensuring that everyone in the EU has access to a fast broadband connection by 2020 and that one in two EU residents uses e-Government services by 2015. Between 2014 and 2020, the Connecting Europe Facility will invest EUR 32 billion in transport infrastructure, EUR 9 billion in energy infrastructure and EUR 9 billion in broadband and digital services. This can help, for example, to reduce driving times to the nearest hospital, which may be located on the other side of a national border, increase the availability and reliability of energy networks and improve access to online services. (2)       Sustainable development Sustainable growth is at the core of Europe 2020 and Cohesion Policy. In the 2014-2020 period, at least 20% of the ERDF in more developed regions and 6% in less developed region has to be invested in measures which improve energy efficiency and expand renewable energy supply. (3)       Functional geographies Functional geography captures the spatial extent of a policy issue, for example, managing a river basin or a labour market area. Using functional geography can enhance the efficiency of public policies, even though it often calls for more coordination across administrative or political boundaries. In the 2014-2020 period, a new measure has been introduced to facilitate the use of functional geography: integrated territorial investment which is intended to make it easier to implement an integrated strategy in a specific area, such as a metropolitan area or a cross-border area. To obtain a better understanding of the functional geography dimension, the Commission has developed a number of new harmonised territorial definitions: ·   Together with the OECD, it has created a new harmonised definition of a city and its commuting area, which shows that the latter, especially in large cities, often cross NUTS-2 boundaries and even national borders. ·   Combining the approach used for the urban-rural regional typology developed in 2010 (EC 2010) and the new city definition, it has also defined a new local typology, the degree of urbanisation, which distinguishes rural areas, towns and suburbs, and cities. This allows for a better monitoring and understanding of the different policy issues facing all types of area, rural as well as urban. To give these typologies more stability and visibility, the Commission intends to include these local and regional typologies in an annex to the NUTS regulation. (4)       Territorial analysis A better understanding of different geographical areas across Europe can help to identify and select the right policy responses and to assess the impact of EU policies with a territorial dimension, as underlined by Member States in the Territorial Agenda and the Committee of the Regions. Since 2010, the Commission has significantly improved the amount of sub-national data available from official statistics through Eurostat and from other sources with the help of the Joint Research Centre, Copernicus, the European Space Agency, ESPON, the European Environmental Agency, the World Bank, the OECD and external contractors. This has led to better data on a wide range of issues including poverty, well-being, health, air quality, innovation, access to public transport and the structure of settlements, but more remains to be done to complete the picture and provide more detail. To support the assessment of territorial impacts[9], the European Commission has invested in better modelling capacity, and projections at sub-national level across the EU can now be generated by a new regional economic model RHOMOLO and a land use model LUISA, while projections of population and education levels have also been improved and updated. 

4.     the economic rationale underlying
the policy has become more integrated

Identifying and understanding the economic
rationale for policy intervention can help to define the goals of Cohesion
Policy more precisely and to identify the best policies for reaching those goals.
The preceding section showed how the general aims expressed in the Treaty have
been interpreted over the years, taking account of the challenges faced by both
existing Member States and by the countries joining the EU. 
The concern here is with the underlying
reasons for regional disparities in economic development. These, it should be
emphasised, can differ between regions in different parts of the EU and are
likely to change over time. For example, the reasons for lagging development in
regions in the UK are different from those in regions in Romania, and the
reasons for lagging development in regions in Spain or Portugal today are not
necessarily the same as they were in the 1980s. 
In the discussions surrounding Cohesion
Policy, there are three main strands of thought about the factors which the
policy should be aimed at tackling. They can be characterised as those that
focus on the ‘first nature’ determinants of development – i.e. those that are
largely inherent in the country or region concerned – those that focus on the
‘second nature’, or human-constructed or influenced, determinants, and perhaps
most importantly in the recent past, those that focus on the impact of trade
and economic integration on development.
The distinction between first and second
nature determinants is somewhat blurred. Some factors cannot be changed at all
(such as the presence of mountains) and are clearly inherent. Others can change
but only over the very long-term, such as the rural or urban nature of a region
or the pattern of settlements, and might be considered as inherent from a
policy perspective to all intents and purposes. Yet others might be capable of
being changed more quickly, though still only over a long period of time, such
as the broad structure of economic activity (which is likely to reflect the
inherent characteristics of regions) or the education attainment level of the
work force, but are more open to policy influence even if any changes achieved
over the medium-term (within say a programming period) are likely to be
relatively small. Still other factors can be changed relatively quickly, such
as access to broadband, and clearly belong to the second nature group of
determinants 

4.1.      Cohesion
Policy has moved beyond first nature determinants of growth

At the origin of many budget policies for
transferring income from leading to lagging regions is the notion that economic
activity, and so the capacity to generate income, will always be depressed in
some regions. This is typically justified by first nature arguments to do with
the inherent features of regions that policy cannot change or at least only
very slowly, such as, for example, their geographic remoteness. 
These arguments have frequently been made over
the years in relation to regional development in the EU. The Treaty refers to a
number of places as worthy of particular attention: 'rural
areas, areas affected by industrial transition, and regions which suffer from
severe and permanent natural or demographic handicaps such as the northernmost
regions with very low population density and island, cross-border and mountain
regions'. Some have argued that these types of area merit separate permanent funds to compensate them for their ‘first-nature’
handicaps. 
Those responsible for the design of Cohesion Policy,
however, have tended to resist such arguments. Although they may seem appealing
and may have merit in individual cases at a given point in time, they cannot be
generalised as condemning a particular type of region to lagging development
for ever. Many places have managed to overcome these ‘first nature’ obstacles
and have succeeded in achieving a relatively high rate of growth and becoming
‘high income’ regions. In a 21st century economy, the inherent
characteristics in question can be as much a stimulus to growth as an obstacle.
This is why Cohesion Policy has focussed more on the ‘second nature’
determinants of development which policy can affect rather than being content
merely to compensate regions for their supposed disadvantages, though at the same
time recognising that these ‘disadvantages’ need to be taken into account when
designing the shape of the policy to be pursued.
It has also focused from the beginning on the
third set of determinants of development, the closer economic integration of regions
across the EU. Indeed, the whole rationale for Cohesion Policy since it was
initiated has been to strengthen the capacity of regions to develop in the
context of a single market in which goods and services are traded freely across
national borders.

4.2.      Cohesion
Policy can boost growth through investment in second nature determinants of
growth 

Economic theory and empirical evidence suggest
several possible reasons for lagging development, which can be identified to
lesser or larger degree as second nature determinants. 
Economic theory and empirical evidence suggest
several possible reasons for lagging development. 
(1)       Under-investment
in public capital stock 
A lack of public capital stock due to
inadequate public investment historically can underlie a significantly lower
level of development. .For example, most of the regions in central and eastern
Europe that used to be behind the iron curtain have a much poorer endowment of
infrastructure. In some countries, public investment has been relatively
concentrated in the regions which include the capital city or are close to it
and regions far from the capital tend to have lower levels of capital stock
which may hinder their development. For example, the capital city region may
have a disproportionately large concentration of universities and research
centres as compared with other parts of the country.
(2)       Low accessibility
The location of a city or region relative to
others determines to a large degree how accessible it is. For example, the
accessibility by road to the rest of the EU will always be less in Northern
Finland and Sweden than in Luxembourg, regardless of the level of investment in
transport infrastructure.
Nevertheless, the accessibility of some regions
or cities is considerably less than it could be if transport links were better.
Improving transport connections would allow producers situated there to compete
more effectively in the Single Market, while at the same time providing easier
access to their markets for producers situated elsewhere so increasing
competition. This would tend to lead to the economic convergence of less
developed regions insofar as the costs of producing there were lower. In
addition, the closer economic integration which would result would tend to lead
to higher overall economic growth in the EU.
(3)       Human capital
The quality of the labour force has a major
effect on productivity and so economic development. High levels of human
capital mean that workers are more efficient and more innovative. In addition,
high levels of human capital can increase the flexibility and adaptability of
the labour force. This makes it easier for an economy to shift to new
opportunities as the market evolves. 
(4)       Innovation
Introducing new products on to the market,
using new processes to produce them and making organisational and marketing
improvements can have a substantial effect on economic development. In the long
run, innovation is the main driver of economic growth. For regions distant from
the knowledge frontier adopting and adapting innovations developed elsewhere
can help them to catch up.
(5)       Low institutional quality
Economic research has undergone an
'institutional turn' in recent years with a great deal of work highlighting the
key role played by the quality of government and the institutional capacity of
public administrations in boosting development. This line of research and the
evidence it has produced demonstrate that low quality of government can
obstruct development and that countries and regions can get stuck in a low-quality
and low-development trap. Most of this research focusses on developing
countries, though it is evident that it can also apply to Europe. 
In addition to the direct benefits that a
high-quality administration can generate, it can also increase its capacity to
identify the right investment mix and use funding efficiently. 
(6)       Agglomerations and clusters
A further reason for under-development is the
absence of agglomerations which can house economic activity and generate the
economic advantages, or economies, of people and businesses being concentrated
in a particular place (urbanisation economies). There are, in addition,
economies to be gained from producers in the same economic sector or in linked
activities being located in close proximity to each other (in clusters or
industrial districts).
Urbanisation economies obviously depend on the
presence of a large city or several cities located close to one another.
Clusters or industrial districts do not necessarily require the presence of a
large city, but they do require a sufficient concentration of enterprises to
generate externalities.
Regions could be affected by the
under-development of one, or more, of these factors. Cohesion policy was
created to assist lagging regions to reduce their development gap compared to
the rest of the EU and it can help to overcome most of the reasons for
under-development. 
The major challenge is to identify the
appropriate policy mix for tackling the factors responsible for lagging
development, which in practice is done jointly by the Commission and the
regions and Member States concerned through dialogue with each other. Depending
on the region, the policy mix may need to focus on human capital, institutions,
infrastructure or innovation or, more usually, some mix of these. The OECD, for
example, has emphasised that investment in transport infrastructure needs to be
accompanied by other measures to improve the productivity of the firms in the
region which is being made more accessible, in order to avoid it losing more of
the local market to producers elsewhere than it gains from being able to export
more easily to other regions. 
The aim of reducing under-development should
not be misunderstood as an ambition to equalise the level of development in all
regions. This would be an impossible and inefficient goal. Some regional
differences in productivity, employment and education will always remain, but
these should not be considered problematic if they do not lead to differences
in well-being or standards of living. Cohesion Policy cannot entirely overcome
the lack of agglomeration economies – urbanisation economies, in particular,
cannot be created without a large city. It can, however, facilitate the
emergence of these economies in existing cities or in a polycentric network of
cities. The benefits from agglomeration might, therefore, be realised through
cooperation between towns or cities or by establishing links between urban
centres or even between urban and rural areas.
The spatial concentration of a sector or linked
economic activities can occur outside large cities. Although some people
question whether public policy can create clusters or industrial districts,
measures to improve the business climate and stimulate innovation might lead to
agglomeration economies emerging in some regions without large cities. 
The impact of agglomeration economies on
regional disparities, however, should not be exaggerated. Within the EU, there
are many regions with high productivity without a large city and many regions
with low productivity despite the presence of a large city. The main reasons
for regional differences in economic development are to do with the capital
stock, technology and human capital; not the presence or absence of a city.

4.3.      Cohesion
Policy supports market integration and can help less developed regions grow
faster

Regional disparities can be viewed as
inefficient or efficient depending on what determines these disparities. If
inefficient disparities can be removed, they will boost overall growth. Trying
to remove efficient disparities, however, will result in a sub-optimal
allocation of resources and so reduce overall growth. 
This is particularly relevant in the discussion
surrounding the expected impact of the single market. In part, Cohesion Policy
was motivated by a fear that lagging regions would lose when joining the single
market. Three economic theories can be linked to radically different views on this.

Neo-classical economic theory would predict
that capital would flow to the least developed regions because it would
generate the highest returns there. For example, it would expect foreign direct
investment (FDI) to go to less developed Member States so boosting their growth
rate. Investment in the public capital stock might lag behind because of the
low level of income in the country, so that it might not, for example, be able
to afford to invest in good transport infrastructure to connect the economy to
the single market. This could depress the return on private investment and slow
down the inflow of FDI. According to this theory, Cohesion Policy could help to
alleviate the funding difficulty and so accelerate the process of convergence. 
When the single market was being created, a new
theory emerged. New trade theory, based on earlier work by Kaldor and others on
increasing returns to industrial production and developed in the 1980s by Paul Krugman,
emphasised that economies of scale mean that regions with a large share of a
particular industry and so tend to benefit more from trade, what is termed the 
home market effect. 
Many supporters of Cohesion Policy, since they
considered that lagging regions would lose out because they lacked economies of
scale, viewed the funding provided under the policy as compensation for regions
likely to face economic decline as a result. So instead of working with market
forces, Cohesion Policy was seen as working against them. Accordingly, Cohesion
Policy was not expected to reduce regional disparities, but to merely to compensate
the regions experiencing relative if not absolute economic decline. The same
argument can be found in the World Bank Development Report of 2009.
The new economic geography, which was developed
in the 1990s by Krugman and others has links with the new trade theory but is more
nuanced  as regards the benefits of trade. While it recognises the importance
of increasing returns to scale, it points to the costs of congestion and  other
factors that encourage the dispersion of economic activities and the shift of
producers out of centres where economic activity is concentrated after a
certain point.
According to this theory, lagging regions might
benefit from being part of a single market but this is not automatically the
case since much depends on the economic conditions in these regions, especially
the business environment, in relation to those in more developed regions. It
is, therefore, considered that Cohesion Policy can potentially help to reduce
regional disparities but should find ways to work with market forces to
strengthen their effect in reducing disparities.
For example, Cohesion Policy can help to improve
the business environment in lagging regions so increasing the likelihood that
they will be more likely to benefit from trade integration. Equally, it can
support improvements in transport and digital connections, enabling scale
economies to be achieved through increased trade and inward investment. Last,
but not least, Cohesion Policy can also help to alleviate some of the
congestion costs in the fast-growing, lagging regions by investing in better
public transport and improvement in urban mobility; thus helping to prolong
this growth by reducing its negative externalities. 

5.     The
division of funding between policy areas has evolved as the goals of the policy
have changed

The way that funding is divided between the
broad policy areas supported by Cohesion Policy depends on the types of region
concerned and their needs and priorities. Investment in infrastructure has
consistently been higher in less developed regions than in others. In the EU-15,
the share of funding allocated to non-environmental infrastructure, amounted to
36% in the 1989-1993 period, though it fell to 23% in the 2007-2013 period as
transport networks were completed. At the same time, support for environmental
infrastructure increased from the 1994-1999 period on following the
introduction of the Cohesion Fund, which raised environmental investment from
less than 2% of Cohesion Policy funding in 1989-1993 to 14% in the next period
and 15% in 2007-2013.
In the other EU-15 regions, the share of
investment in (non-environmental) infrastructure rose from 5% in 1989-1994 to
13% in 2007-2013, in part due to increased investment in renewable energy from
2000 on, while  environmental investment also increased, from 8% to 14% of
total funding.
By contrast to infrastructure, investment
in human capital was consistently higher as a share of total funding in the
other EU-15 regions than in less developed ones, though it varied between
periods. It increased from 39% of total funding in 1989-1993 to 57% in 1994-1999,
mirroring a reduction of similar size in the share going to business support.
It then declined to 46% in 2000-2006 and 35% in 2007-2013 as support, first,
for infrastructure and then for the environment increased. On the other hand,
the share going to business support rose slightly from 31% in 1989-94 to 34% in
2007-2013
In less developed regions in the EU-15, the
share of funding going to human capital fluctuated less between periods,
varying between 21% and 25% and accounting for 22% of the total in 2007-2013.
The share of funding going to the business support was much the same as in the
other EU-15 regions over the last three programming periods, accounting for 34%
of funding in 2007-2013 after falling to 28% in the previous period.
Table
6: Cohesion Policy funding
by broad policy area in EU-15, 1989-2013
   || Less developed regions & CF ||   || Other regions 
   || 1989-1993 || 1994-1999 || 2000-2006 || 2007-2013 ||   || 1989-1993 || 1994-1999 || 2000-2006 || 2007-2013 
 Business support (including - RTDI) || 31.5 || 33.0 || 28.0 || 34.4 ||   || 48.1 || 31.1 || 29.2 || 33.8 
 Infrastructure (Transport, Energy, Telecom, Social infrastructure) || 36.3 || 26.1 || 30.9 || 23.2 ||   || 5.2 || 1.5 || 13.4 || 13.2 
 Human Capital (labour market, education, social inclusion etc.) || 20.6 || 24.7 || 24.5 || 22.3 ||   || 39.0 || 56.8 || 45.8 || 34.6 
 Environment || 1.6 || 14.3 || 14.0 || 15.4 ||   || 7.6 || 9.8 || 8.6 || 14.2 
 Other || 9.7 || 1.9 || 0.8 || 0.4 ||   || 0.0 || 0.8 || 1.1 || 0.3 
 Technical assistance || 0.4 || 0.0 || 1.8 || 4.3 ||   || 0.0 || 0.0 || 1.8 || 3.8 
 TOTAL || 100 || 100 || 100 || 100 ||   || 100 || 100 || 100 || 100 
 Source: Structural Fund reports, SFC and REGIO calculations 
The distribution
of Cohesion Policy funding between policy areas in the countries that acceded
to the EU in 2004 and 2007 is very different from that in the EU-15, even in
the less developed regions. These countries have allocated a much larger share
of funding to infrastructure and the environment (in practice, mostly
environmental infrastructure), especially in the period 2004-2006, reflecting
the very low levels in terms of quality as much as amount, and, consequently,
their far greater need for investment to comply with EU Directives (see below).

As a consequence, the share of funding
allocated to business support (26% in 2007-2013) and human capital 13%) was
substantially lower than in the EU-15, though there was some shift from
infrastructure to business support in the 2007-2013 period (from 14%).
Table 7 Cohesion Policy funding by broad policy area in acceding countries,
2004-2013
   || EU-10 || EU-12 || 
   || 2004-2006 || 2007-2013 || 
 Business support (including RTDI) || 14.2 || 25.6 || 
 Infrastructures (transport, energy, telecoms, social infrastructure) || 41.5 || 36.1 || 
 Human Capital (labour market, education, social inclusion) || 14.8 || 12.5 || 
 Environment || 27.3 || 20.8 || 
 Other || 0.1 || 0.0 || 
 Technical assistance || 2.1 || 5.0 || 
 TOTAL || 100.0 || 100.0 || 
 Source: Structural Fund reports, SFC and REGIO calculations   Box on Financial instruments in 2007-2013 Financial instruments (FIs), in the sense of revolving or recyclable funding to complement non-refundable grants, have been part of Cohesion Policy since the 1994-1999 programming period and have expanded in terms of variety, scope and amount since then. The flexibility which they involve in providing support to Member States and regions has been especially important in the uncertain economic circumstances of the past few years. FIs have to conform to the logic and legal framework of Cohesion Policy, including shared management and the principle of subsidiarity. Policy intervention occurs mostly in regions where there are obstacles to development in the form of low administrative capacity, a shortage of entrepreneurs, underdeveloped financial markets and so on. FIs can help to tackle these obstacles by: ·   providing a range of forms of financial support, including equity, loans, guarantees and micro-finance to enterprises (primarily SMEs) as well as for urban development and energy efficiency or renewable energy projects; ·   enabling public resources to be used more efficiently by drawing on commercial practices and expertise and by attracting private capital, in part by absorbing some of the risks of investment; ·   enabling the same funds to be used several times over so increasing their effects, which is particularly important in times of budget constraints; ·   giving an incentive to recipients to use the funding efficiently in order to be able to pay it back. As the use of FIs has increased during the 2007-2013 period, there has been a growing need to learn from experience and adjust the legal framework, harmonise the rules and offer more detailed guidance on their deployment. Audits carried out by the Commission, Court of Auditor reports and studies and observations by the European Parliament and the institutions involved in the management of FIs have pointed to the challenges that need to be tackled before FIs can fully affect the pursuit of Cohesion Policy objectives. Since the 2007-2013 legislation came into force, the Commission has taken several steps (by amending the regulations, issuing guidance notes, carrying out evaluations and offering technical assistance) to strengthen and clarify the rules on FIs. According to the latest data reported by Member States, around 5% of ERDF allocations for 2007-2013 had been committed to more than 900 FIs in 175 OPs in 25 Member States (all except Ireland and Luxembourg) by the end of 2012. Support from the ERDF and, to a minor extent, the ESF, amounted to EUR 8.4 billion, most of it going to enterprises. Over 144, 000 separate instances of investment projects in businesses had occurred and over 40,000 gross jobs were reported to have been directly created through FIs. Some EUR 744 million of the Structural Funds has also gone to co-finance FIs providing funding for urban development and energy efficiency and/renewable energy projects in 19 Member States. Recent data indicate that on average each EUR 100 of the Structural Funds going into FIs have led to EUR 150 of national public and private co-financing. This rate should increase over time as the funds are recycled. Data also indicate, however, that almost EUR 8 billion of OP funding remained in FIs and had still to reach final recipients at the end of 2012. In a number of Member States, efforts, therefore, need to be stepped up to ensure that this funding reaches final recipients by the end of 2015 (i.e. the date by which funding for the 2007-2013 period has to be spent). 

6. The
impact of the crisis on the 2007-2013 period 

The economic and financial crisis hit the
operational programmes planned for the 2007-2013 programming period early on.
Although EU regional policy is designed as a long-term structural policy,
action was required to adapt to a widely different economic context and to
respond to unexpected challenges.
At the operational level, a number of
programmes experienced a mismatch between the funding allocated and the demand
for it or a radically different local context. For instance, a decline in
demand for support was registered in certain policy areas and an increase in
others. In many programmes, there were problems finding the necessary national
or regional co-financing and coping with exchange rate variations (in Poland and the UK especially), though there were also reductions in construction costs which reduced
the cost of some projects (such as in Bulgaria and Poland).
A number of innovative measures, both
regulatory and at the programme level, were implemented to accelerate the
disbursement of the Structural Funds and to make them more flexible and
responsive, especially in the most vulnerable Member States. The Commission
provided support to Member States on reprogramming, including in the form of
Task Forces (e.g. to help Greece implement the EU-IMF adjustment programme and
speed up its absorption of EU funding). In February 2012, action teams were set
up in 8 Member States (Ireland, Italy, Latvia, Lithuania, Portugal, Slovakia and Spain as well as Greece), with representatives of national and Commission
officials.
Almost 13% of the total funds (EUR 45 billion )
has been shifted from one policy area to another since 2009 to meet the most
pressing needs and to strengthen particular interventions which had shown
themselves to be effective (see Figure 84). The main increases in funding were
for R&D and innovation, generic business support, sustainable energy, roads
and the labour market, in particular measures to increase youth employment. The
main reductions were on ICT services, environmental investment, railways,
training, education and capacity building. 
By 2013, about EUR 17 billion of EU financing
had been targeted for accelerated delivery or reallocation, which might help
around 1 million more young people and 55,000 SMEs.
Figure 11: Share of EU funding reallocated between policy
areas
The Commission has encouraged simplification or
rationalisation of national and regional procedures to ensure faster
implementation of programmes by paying advances to public authorities and
increasing those to enterprises under state aid schemes (in 10 Member States).
In order to improve the cash flow of managing authorities, the Commission has
provided additional advance payments of EUR 7 billion[10]. 
In addition, national co-financing rates have
been reduced for a number of Member States, especially those most affected by
the crisis, to take pressure off national budgets This has reduced the national
public spending requirement significantly from EU 143 billion to EUR 118
billion, i.e. a reduction of 18%, which has cut the overall amount of public
investment carried out but which has helped to secure the completion of
projects already planned and to improve cash flow in the countries concerned. 
Figure 12: Reduction
in national cofinancing to end 2013
The EU has also approved further reductions in
national co-financing by temporarily increasing EU co-financing rates by 10
percentage points for Member States with the greatest budget difficulties (the
so-called ‘top-up’ for countries with adjustment programmes). The ‘top-up’
provision has enabled payments to be made to these countries at an earlier time
than originally anticipated, so easing the pressure on national budgets
and providing much-needed liquidity. By the end of 2013, almost EUR 2.1 billion
had been paid as ‘top up’.
The ‘top-up’ reduces the national contribution to
Cohesion Policy programmes and so eases the burden on national budgets at a
time when they are under extreme pressure and provides much-needed liquidity 
Major results are still expected from the
2007-13 Cohesion Policy programmes over the next 18 months. By end-2012, the
projects selected were reported to account for around EUR 292 billion, or 84%
of available EU funding. In some Member States, however, there are serious
delays in both project selection and initiation, especially in areas such as
RTDI, railways, ICT and broadband, energy and capacity building, where
authorities have less experience or projects are relatively complex to carry
out. 
Recent payments data underline the need for
efforts to complete the 2007-13 programmes to be stepped up. By May 2014, EUR 108
billion, or 32% of total funding available for the period, was still left to be
paid by the Commission to Member States. Lower payment rates were registered
for Romania, Slovakia, Bulgaria, Italy and Malta (see Figure 86). While there
is an inevitable delay between expenditure taking place on the ground, it being
declared to the Commission and payment being made, there is a growing risk that
some Member States and regions will lose a large amount of funding because of
not being able to complete programmes by the end of 2015. There is a serious
possibility, therefore, that they will fail to achieve their intended policy
aims unless things speed up markedly.
Figure 13: Funding
absorption and project selection by Member States for the 2007-2013 programming
period
 

6.1.      ESF
and the reaction to the crisis[11]

The role of the ESF in response to the crisis
varied across the EU according to the way labour markets were affected, the
support already in place and the specific measures implemented in the different
countries.
Labour market developments
The impact of the crisis on employment differed
significantly between Member States, reflecting the way different sectors were
affected by the crisis as well as the policy responses to it. Over 5 million
jobs were lost in the EU-27 between the third quarters of 2008 and 2009, though
these were unevenly spread across Member States. After 2009, developments in
countries continued to diverge, with some experiencing economic growth and
others further decline. As employment has fallen less than GDP over the crisis
period in a number of countries, the full impact of the economic downturn may
still be to come. 
National policy responses and the role of
the ESF
When the crisis began, a European Economic
Recovery Plan was launched which included recommendations for labour market
policy measures in Member States. In most countries, recovery packages were
introduced to counter the effects of the recession. A range of active labour
market measures were implemented, including short-time working arrangements,
temporary wage subsidies, reductions in non-wage labour costs, increased public
sector employment and training programmes. The last accounted for around a
third of the increased expenditure, while a quarter went on employment
initiatives and smaller amounts on direct job creation and business start-ups. 
The ESF provided support to training, in
particular, giving the opportunity of those on short-time working arrangements
to upgrade their skills at the same time. It also co-financed measures to
create or maintain employment, such as apprenticeship schemes and recruitment
incentives. 
Some shifts in the allocation of funding
occurred in Member States over the period in response to the crisis, partly to
assist sectors that were badly affected (such as construction and parts of
manufacturing). Indeed, one effect of the crisis has been to raise awareness of
the consequences of a severe economic downturn for employment in major sectors
of the economy as well as for particularly vulnerable social groups.

7.     Conclusion

The above represents an overview of how the
goals of Cohesion Policy have evolved over time and how they have become more
closely linked to the overall strategy of the EU. This has had clear
repercussions on the types of action supported by Cohesion Policy with an
increasing share going to environmental projects and more funding being linked
to the Lisbon, Gothenburg and the Europe 2020 strategies.
The geography of Cohesion Policy has been
simplified since 2007 to ensure that it can cover all regions while increasing
the efficiency of implementation. 
Successive enlargements have changed the
challenges which Cohesion Policy is aimed at tackling and increased the
difficulty of overcoming them. Not only have they led to regions with low
levels of development being added to the EU, but they have increased its
territorial diversity.
With the introduction of territorial
cohesion as an explicit objective in the Lisbon Treaty, Cohesion Policy has
placed a stronger emphasis on sustainability and access to basic services, on
the need to take account of functional geography and on the importance of
territorial analysis. This is mirrored in the increased focus on sustainable
growth in Europe 2020 and in the recognition of the importance of moving beyond
GDP when assessing territorial development. ESPON has responded to the need for
more territorial analysis with support for applied research targeted on
relevant issues. 
The debate on how to measure progress and
how Cohesion Policy should respond to this is still ongoing. The outcomes of
this debate are likely to influence the shape of Cohesion Policy after 2020 as
well as perhaps how policy is implemented in the current period.
[1]       Data on funding distribution by type of region is not
available prior to 1989 as no regional categorisation was used prior to 1989.
[2]       The aid intensity of more developed regions covers Objective
2 and 3 in 2000-2006 and Objective 2, 3, 4 and 5b in 1994-1999. Objective 2 and
5b were geographically more concentrated and so the areas eligible for support
had much higher aid intensities than reported here.
[3]       TFEU Article 39(2)
[4]       Article 2 of Regulation (EU) No 1305/2013 of the European
Parliament and of the Council of 17 December 2013 on support for rural
development by the European Agricultural Fund for Rural Development (EAFRD) and
repealing Council Regulation (EC) No 1698/2005, OJ L 347, p. 487.
[5]
 Source: European Commission, 2011 EAGF Financial Report.
[6]       These are largely ‘decoupled’ in the sense that direct
payments support farmer incomes without being related to production ,in return
for them respecting standards of food safety, environmental protection and
animal welfare and keeping the land in good condition.
[7]       For MS that did not select a national target for an
indicator, a target was imputed based on the targets of MS with a similar rate
in 2009. For more information see (Athanasoglou and Dijkstra 2014).
[8]
      CoR works on the mid-term
assessment of Europe 2020 have included 7 Flagship Initiative conferences and
surveys as well as 4 specific workshops/seminars involving more than 1750
participants as well as a broad survey among local and regional authorities with
more than 1000 respondents (http://portal.cor.europa.eu/europe2020/Pages/welcome.aspx ).
[9]       See also: CSWD 2013/: Operational guidance on how to include
a territorial dimension in the Commission’s Impact Assessments. http://tobecompleted
[10]     This amount includes the additional pre-financing introduced by
Council Regulation (EC) No 284/2009 as well as another EUR 775 million provided
by amending regulation (EU) No 539/2010. Which was also intended to improve
liquidity for Member States, 
[11] http://ec.europa.eu/social/BlobServlet?docId=7671&langId=en

Chapter 7 Impact of Cohesion Policy

1.     Introduction 

A number of sources provide information on
the effect of Cohesion Policy on the objectives of the programmes which it
co-finances. These give an indication of the extent to which Cohesion Policy is
successful in achieving these objectives as well as the broader policy goals of
strengthening the capacity of national and regional economies for sustainable
development and furthering economic, social and territorial cohesion. 
In the first place, there is quantitative
information on the direct outcomes of the projects and measures supported from
the physical indicators which are monitored by Managing Authorities responsible
for the programmes. The indicators are usually in the form either of the output
produced (such as the number of new businesses helped to start up, the length
of road or railway constructed or the number of people trained) or the results
which they have given rise to (such as the time or travel costs saved as a
consequence of a new city ring-road being opened, the number of people
connected to main drainage and an effective system for treating wastewater or
the number of people trained who succeed in getting jobs). 
Secondly, there is the evidence from
evaluations of particular programmes or interventions in particular policy
areas (such as support for enterprise development or RTDI) which are aimed at
assessing the effectiveness of the funding provided in achieving both the
immediate objective of the measure (such as increasing the investment of the
companies supported or their expenditure on R&D) and the wider aim of
strengthening the development potential of the places concerned (such as
through increasing the competitiveness of the businesses located there or the
skills of the work force).
Thirdly, there is the evidence from
macroeconomic models which attempt to capture the way that economies function
in order to estimate the effect of Cohesion Policy, and the programmes it
supports, on the main economic variables, in particular, on GDP, employment and
trade performance. This they do essentially by simulating the way the economy
would have developed (or is likely to develop in the future) in the absence of
Cohesion Policy which can then be compared with the way that it actually
developed (or is projected to develop). To do so requires incorporating in the
model the evidence from evaluations and other studies on both the immediate and
wider effects of policy interventions on company investment, RTDI, the skills
and productivity of the labour force as well as of businesses, the reduction in
transport costs from the new roads, railways and other infrastructure built and
so on.
Last but not least, there are smaller
independent research studies which mostly use econometric techniques to assess
the overall effects of Cohesion Policy on regional developments. 
All four sources are important for
assessing the overall impact of Cohesion Policy on its objectives. The sections
below summarise the available evidence in these four areas. The focus is on the
last programming period, 2007-2013, though evidence is also referred to from
earlier years, not least because the 2007-2013 period does not formally finish
until the end of 2015 and programmes are still underway. More fundamentally,
many of the projects supported are long-term ones intended to affect the
structure of economies, to change the way that businesses operate and
individuals behave and perform and to strengthen the capacity to sustain
growth. Accordingly, the observable effects in terms of an improvement in
economic performance will materialise only after a number of years and the data
to detect them will come available even later. 

2.     The
results of programmes in 2007-2013

This section provides an overview of the
results reported by Cohesion Policy programmes in their annual implementation
reports. The first section covers the ERDF and Cohesion Fund, the second the
ESF. 

2.1.      The European Regional
Development Fund and Cohesion Fund

As noted above, the programmes co-financed
under Cohesion policy in the 2007-2013 period are still underway and many
projects are still to be completed. Nevertheless, it is possible to identify
the outcomes up to the end of 2012 (the 6th year of the period and the latest
date for which data are available) from the support provided by the ERDF and
Cohesion Fund on the basis of the physical indicators of the output and results
of the expenditure undertaken which are maintained by Managing Authorities. The
data that they have reported is summarising below, focusing on the core
indicators which are intended to be comparable across programmes so that the
data can be aggregated both at the national and EU level.

2.1.1.   Gross
jobs directly created

The data reported on programmes indicate that
up to the end of 2012, when in most countries half or less of the funding
available for the period had been spent, some 593,954 jobs had been directly
created across the EU by ERDF co-financed interventions. This represents 43% of
the target set at the beginning of the period, suggesting that by the end of
2015 there might be close to 1.4 million new jobs as a direct result of ERDF
support. Many these jobs were created – some 320, 000 overall – in the less
developed (Convergence) regions where there is a particular need for
employment, and where, if the targets are met, the figure could reach 900,000
by the end of 2015.
These figures, it should be emphasised relate
to gross jobs – i.e. they do not take account of any jobs displaced – and
essentially refer to the additional number of people employed in the projects
supported, or in most cases, in the enterprises receiving support. Many of
these jobs might well have been created in the absence of support, in the sense
that, for example, companies might have gone ahead with their investment plans even
if they had not received public funding, though perhaps on a smaller scale with
a smaller work force. Nevertheless, a substantial number of the additional jobs
almost certainly would not have been created without EU support. The evaluation
evidence summarised below indicates that this is the case. Moreover, the
figures do not include jobs indirectly created as a result of the projects
undertaken and the improvements in competitiveness which they give rise to,
which, as the macroeconomic models show, are likely to materialise in the
longer-run.

2.1.2.   Enterprise support

A large number of the jobs created were in SMEs
which received a major proportion of the support provided, in the main to
improve their efficiency through helping them to invest in new machinery and
equipment or to develop new products. In total across the EU, some 200,000
projects to support investment in SMEs were undertaken up to the end of 2012.
In addition, almost 78,000 new firms across the EU were helped to start up by
the financial assistance received from the ERDF as well as by the advice and
guidance provided by business support centres also funded by the ERDF (see Box
for specific examples of the measures supported).
An increasing amount of the support provided
was in the form of financial (engineering) instruments, such as loans,
interest-rate subsidies or venture capital, which have the advantage of helping
firms overcome constraints on borrowing while being repayable (and perhaps even
yielding a rate of return), so potentially enabling the funding going into them
to be used multiple times. Because they are repayable, they also give the
companies receiving support an added incentive to ensure that the investment
concerned is successful.

Box - Examples
of enterprise support schemes

Greece: Funding was provided to around 1,300 SMEs
under the JEREMIE financial instrument scheme, mainly in the form of loans, so
helping them to overcome the tight borrowing limits imposed by the financial
market.
Portugal: Up to mid-2013, some 9,458 companies had
been supported by business aid schemes co-financed by the ERDF and 952 new
businesses had received financial help to start up, 448 of them in high-tech or
knowledge intensive sectors.
Belgium: Financial
instruments, in the form of risk capital, loan-guarantees, micro credits and
‘mixed products’, which were co-financed by the ERDF, helped 571 new businesses
to start up and 671 firms to expand up to the end of 2012, over 10 times the
number assisted by investment grants.
Bulgaria: Under the JEREMIE scheme, some 1,388 SMEs
had received low-interest loans by the end of 2012, helping to them to overcome
the squeeze on credit in the financial market.
Malta:
The First Loan Portfolio Guarantee scheme, co-financed by the ERDF, had
provided funding to 533 SMEs by mid-2013, so alleviating their difficulties of
borrowing on the financial market.

2.1.3.   Support
for RTDI

Over 21,600 projects were co-financed up to the
end of 2012 to support cooperation between research centres and businesses
aimed at ensuring that the R&D undertaken in the former has the best chance
of being transformed into new, or improved, products and processes which can
enable enterprises to maintain or expand their market share in both the
regional and wider market-place.
At the same time, support was provided to some
61,200 RTDI projects, which, together with support for other measures, led to
21,000 research jobs being created, around half of them in less developed
regions.
Examples of RTDI projects supported
Spain: 5,839 large projects were co-financed up
to the end of 2012 to support the R&D carried out in the public sector,
these representing a significant proportion of the projects initiated under the
National RTDI Plan. 
France: The ERDF
provided support to the 71 ‘Pôles de compétitivité’ which were set up to
bring together clusters of businesses, research laboratories and universities,
each specialising in a particular broad sector of activity. According to an
evaluation in 2012, they had been responsible up to then for over 2,500 innovations
since they were established. 
Czech Republic: The ERDF co-financed 53 new
Centres for Technology Transfer, Centres of Excellence and Science and Technology Parks.
Slovenia: The ERDF co-financed 8 Centres of
Excellence, 7 Competence Centres and 17 Economic Development Centres up to the
end of 2012.
Romania: 253 R&D centres were either newly
built or modernised with the aid of EU funding.

2.1.4.   ICT
infrastructure           

The ERDF was also used in many parts of the EU
to support the use of ICT by SMEs, the introduction digital means of accessing
public services and investment in broadband to improve access to the internet,
or in some cases to provide access where none existed before. Up to the end of
2012, this investment had led to over 5 million additional people gaining
access to broadband, around half of them in less developed regions, so reducing
the digital divide which is still relatively wide in a number of countries,
especially in the EU-12 and southern EU-15 Member States.
Examples of ICT projects supported
Greece: Almost
730,000 additional people were given access to broadband as a result of ERDF
financing, most of them in the Macedonia and Thrace region, which is one of the
least developed in the country, so helping to narrow the digital divide.
Spain: Major support from the ERDF was given to
computerisation in public administration, education, healthcare and legal
services as well as to the spread of ICT in SMEs.
Romania: Projects supported by the ERDF resulted in
over 560,000 people using e-Governance, e-Health and e-Learning online systems
by the end of 2012.

2.1.5.   Transport

Nearly 2,550 km of new roads were constructed
by projects co-financed by the ERDF and Cohesion Fund up to the end of 2012,
almost all of them in less developed regions in the EU-12 where the road
network is most in need of improvement after many decades of neglect. Some
1,200 km of these consisted of motorways which are part of the TEN-T system. In
addition, around 17,000 km of existing roads were improved – either widened or
turned into dual carriageways, for example – again mostly in the less developed
regions, where in many cases, especially in the EU-12, the state of the roads
and the limited number of motorways and by-passes around cities lead to heavy
congestion and slow journey times. Both forms of investment have led to
significant time-savings in many cases as well as improving links between
centres of population and economic activity both within countries and between
them. The new roads constructed have also in a number of cases taken traffic
away from city centres and so reduced pollution as well as congestion and
improved the quality of life there.
While relatively few new railway lines were
constructed over the period up to the end of 2012, there were significant improvements
made to existing lines, through electrification, the installation of modern
signalling, conversion of single to dual track and so on. In total up to the
end of 2012, 2,369 km of railway lines are reported to have been improved, once
more mainly in less developed regions. In addition, through both the
construction of new lines and upgrading existing ones, almost 1,500 km was
added to the TEN-T rail network, in this case mainly in EU-15 Convergence
regions. A number of public transport projects in cities were also supported
over the period, perhaps most notably the Sofia metro system in the Bulgarian
capital which has led to a significant reduction of congestion in the city.
A large number of other projects designed to
improve the transport system, and in some cases, to reduce the damaging effects
on the environment, were carried out across the EU up to the end of 2012, in
respect, in particular, of urban transport, ports and airports, though their
diverse nature makes it difficult to aggregate the outcomes (see Box for a few
examples).
Examples of transport projects supported
Portugal: The roads constructed as a result of ERDF
and Cohesion Fund support include the last section of the inner ring-road
around Lisbon, which carries an average of 50,000 vehicles a day and which has
reduced the traffic on the main roads in the capital by 40%, so improving the
urban environment.
Bulgaria: EU funding co-financed the construction of
the second Metro line in Sofia together with 13 new stations, two on the first
line and 11 on the second line. The line has relieved traffic congestion in the
city and made it easier to move around it.
Estonia:
Improvements in the rail network co-financed by the EU led to a 31% reduction
in travel time up to the end of 2012; the aim is to reduce it further, by 45%
overall by the end of 2015.
Hungary: EU funding co-financed a section of the M0
motorway around Budapest helping to reduce congestion in the city, while
improvements in the rail network led to a 47 minute reduction in the average
duration of journeys on TEN-T lines.
Poland: EU funding helped to redevelop and
modernise Wroclaw airport with the construction of a new terminal fitted with
modern facilities, including an automated luggage control system.
Romania: Some 124 km of new motorway was
constructed with EU support up to the end of 2012 and an additional 387 km are
expected to be completed by the end of 2015. When finished, a motorway will
link the Black Sea Coast and major cities across the country, including Bucharest,  Sibiu and Arad, with Hungary and the main cities in Central Europe.
 Improving the quality of major project applications JASPERS (Joint Assistance to Support Projects in European Regions) has made an important contribution to improving the quality of Major Project applications in the EU-12 by helping the Member States concerned prepare projects properly, in a way which demonstrates that the expected benefits outweigh the costs. The European Investment Bank (EIB) is the largest single co-financer of EU-funded programmes and is actively engaged in administrative capacity building initiatives in a number of countries, including Greece, Bulgaria and Romania. Special Task Forces were set up in the previous programming period combining Member States, International Financial Institutions, the Commission and other experts to act as a ‘fire brigade’ for programmes with urgent problems (such as in the southern Italian regions, Bulgaria and Romania). Funds earmarked for technical assistance were used to finance reviews of particular policy areas as well as action for specific projects led by the EIB, the World Bank and the European Bank for Reconstruction and Development. In Romania, a special initiative was launched to improve public procurement procedures, involving DG Regional Policy, DG Internal Market and JASPERS. 

2.1.6.   Environmental
infrastructure

Up to the end of 2012, around .3.3 million
people across the EU were provided with an improved supply of drinking water as
a result co-financed projects. These were for the most part in less developed
regions (2.7 million of the total), especially in Convergence regions in Spain (where 1.7 million people were connected to an improved supply). 
In addition, some 5.5 million people were
connected to improved wastewater treatment facilities, mainly through
installing main drainage and sewage treatment plants, so helping to protect the
environment and strengthening the prospects for sustainable development. These
again were mainly in less developed regions in the EU-15, in Spain (where 2.2 million people were connected) and Italy (1.1 million), in particular.
Some 2,126 projects were carried out, with the
support of EU funding, to recycle both municipal and industrial waste, to
increase waste storage facilities and landfill capacity and to close
sub-standard sites, almost all of them in Convergence regions and many in the
EU12. 
Projects to implement flood prevention measures
co-financed by the ERDF resulted in increased protection for around 4.2 million
people across the EU in both Convergence and Competitiveness regions.
Examples of environmental infrastructure projects supported
Portugal: Some 239 wastewater treatment plants were
constructed up to the end of 2012 with the support of EU funding together with
around 1,425 km of main drainage pipelines, serving around 820,000 people, and
640 km of mains water supply, bringing improved drinking water to over 273,000
people.
Italy: Projects co-financed by the ERDF resulted
in over 1 million people being connected to improved wastewater treatment
facilities, around 13% of the total population in Convergence regions and
nearly 40% of that in Sicily and Basilicata where most of the investment was
carried out.
Malta: The South
Sewage Treatment Plant built with the aid of EU funding, which is capable of
treating 80% of the sewage generated on the island, led to the status of
coastal waters in the south of the country being raised from Class 3 to Class 1
and to Malta becoming the first Mediterranean country to treat all wastewater
before it is discharged into the sea.
Slovakia: EU funding co-financed the construction or
modernisation of 89 differentiated waste collection facilities, increasing the
amount of waste recovered by 15,699 tons a year.

2.1.7.   Renewable
energy and increased energy efficiency

A large number of projects (some 29,358 in
total) were carried out with ERDF support to increase electricity generating
capacity from renewables. Over 80% of these were in less developed regions,
though more in the EU-15 than in the EU-12. Altogether they resulting in
generating capacity being expanded by 2,431 MW, contributing significantly to
the EU-wide target of increasing the energy produced from renewables to 20% by
2020.
In addition, a great many of projects were
carried out to increase the energy efficiency of apartment blocks and public
buildings especially in the EU-12 countries where both types of building are
heavy consumers of energy, partly because of the construction methods used and
the decades of neglect during the previous regime.
Examples of energy projects supported
Austria: Projects supported led to generating
capacity in 55 plants using biofuels being increased by 89 MW or by 20%,
resulting in a potential reduction in greenhouse gas emissions equivalent to
the CO2 produced by around 33,000 cars.
Lithuania: 706
public building had been renovated and their energy efficiency increased by the
end of 2012.
Latvia: A great
deal of social housing was renovated with a view to improving energy
efficiency; overall, an average reduction in heating costs of over 45% was
achieved as a result of the work carried out 

2.1.8.   Tourism, cultural activities,
social infrastructure, land reclamation and urban renewal

Projects carried out in other policy areas, in
addition to those considered above, cover a range of different types, including
those supporting the development and expansion of tourism, local amenities, the
cleaning up of contaminated land, especially old industrial sites, the
renovation of buildings and urban areas, the construction and modernisation of
hospitals, health centres, schools, community centres and other social
infrastructure and local amenities. While the projects are often small in
scale, they can have a significant effect in improving the quality of life in
local communities as well as contributing to the development of economic
activities. 
Because of their nature, however, the outcome
of the investment carried out is in many cases difficult to capture through
physical indicators – such as an improvement in the urban environment or in
local amenities or the safe-guarding of cultural traditions or historical
monuments, which are important to preserve for future generations as well as
present ones (though they also might have the potential to attract tourists). Most
of the physical indicators used in practice relate to the number of projects
carried out, which, in themselves, of course, convey little about the output or
the results of the expenditure concerned.
The main outcomes up to the end of 2012,
insofar as they can be identified and aggregated across countries, include:
·   Over 8,600 projects co-financed by the ERDF carried out across the
EU to support tourism, most of them (around 75%) in Convergence regions in the
EU-12, which directly created a reported 11,928 jobs in total. 
·   The reclamation of some 576 sq. km of polluted land, most of it in
Convergence regions and around two-thirds in Hungary, Spain and Italy. 
·   The co-financing of around 3,800 projects across the EU to expand or
to improve healthcare facilities, most of them in Convergence regions. 
·   The support of some 19,043 projects for investing in education
facilities, to build new schools or colleges or to modernise and re-equip
existing ones, which were almost entirely in Convergence regions, mainly in the
EU-15. 
Examples of tourist, cultural, social and educational infrastructure
and urban projects supported 
Italy: The ERDF co-financed the upgrading of ICT
and science facilities in 80% of all primary and secondary schools in
Convergence regions in the south of the country. 
Portugal: Under the Schools Modernisation Programme,
co-financed by the ERDF, some 867 schools and facilities in schools were either
newly built or expanded or renovated.
France: A branch of the Louvre museum was opened
in Lens, in the Nord-Pas-de-Calais, with ERDF support.
Austria: The ERDF helped to finance the
regeneration of around 28,500 square metres of public space in Vienna.
Hungary: Some 136 nurseries and primary and
secondary schools housing over 12,000 children were renovated with ERDF
support.
Romania: The ERDF co-financed the renovation of
much of Alba Iulia in Transylvania, including the citadel, making the city one
of the most attractive tourist centres in the region. As a result, the citadel
museum recorded an increase in the number of visitors from 21,900 in 2010 to
over 45,000 in the first 9 months of 2013 alone. 
Slovenia: Some 146 projects were carried out to
improve tourist facilities, including the renovation of 20 cultural heritage
sites. Although there is not necessarily a causal link, the number of overnight
stays increased from 7.6 million in 2007 to 9.5 million in 2012 and over
457,000 people visited the renovated sites.
Slovakia: The ERDF co-financed the expansion and
modernisation of healthcare facilities, the number of hospital beds being
increased by 2,022 and 664,541 patients being treated in modernised facilities.

2.2.      The European Social Fund
2.2.1.   Access to employment

ESF support was equivalent to around 20% of
total Active Labour Market Policy expenditure in Member States in the 2007-2013
period, ranging from 2% in high income countries to over 100% in low income,
‘Convergence’ ones.
·   ESF supported at least 19.6 million ‘participations’ (i.e. cases of
participation in programmes) aimed at enhancing people's access to employment
up to the end of 2012[1],
around 3.3 million of whom found a job soon afterwards. In most Member States,
the proportions finding a job and those still in it after 6 or 12 months have
been close to the targets set.[2]
In addition, over 497,000 cases of people attaining qualifications were
reported, while nearly 42,000 people moved into self-employment. 
Support was also provided to help people into
employment, especially people with disabilities, other disadvantaged groups,
ethnic minorities, migrants, women and young people. The crisis made it more
difficult in many countries for people to find jobs and remain in them and some
programmes were modified as a result.
Up to the end of 2012, over 20 million young
people under 25 received support, nearly 30% of the total, though in southern
Member States, the proportion was smaller despite large numbers of young people
not being in employment, education or training, reflecting the even larger
numbers of those aged 25 and over being out of work. 
Evaluations[3]
in 5 Member States (Austria, the Czech Republic, France, Italy and Portugal) indicate that Cohesion Policy programmes strengthened their focus on young
people after the crisis hit. All five gave priority to helping those at risk of
leaving school early or who had already dropped out of school and four of them
(all except Portugal), to young people not in education, employment or training
(what are known as NEETs).
Youth Action Teams
In 2012, the Commission established joint Youth Employment Action Teams
in the 8 Member States with the highest levels of youth unemployment. Cohesion
Policy funding for the 2007-2013 period, which remained unallocated, was used
to increase job opportunities for young people and to facilitate the access of
SMEs to finance. Over one million young people are expected to be helped from
the EUR 4.2 billion allocated (EUR 1.4 billion of which has already been
committed to projects).
From 2009 on, more resources were used to support
self-employment and business start-ups and to develop intermediate labour
markets, which provide long-term economically inactive with work placements,
training and qualifications.

2.2.2.   Social inclusion policies

Social inclusion was a more important objective
in the 2007-2013 period than previously. The ESF gave support to measures
providing ‘pathways to integration’ and the re-entry of disadvantaged groups
into the labour market[4].

Up to the end of 2012, EUR 12.9 billion was
invested in social inclusion measures and a further EUR 10.3 billion had been
committed to these[5].
Results are available for only a few Member States ,
but available figures indicate that the number finding employment has been substantial,
with over 164,000  reported (though the vast majority of these are in Spain). The
number gaining a qualification is also substantial, with nearly 148,000 cases
of people gaining qualifications being reported.
Support was also targeted on combating poverty
among the most vulnerable groups, such as migrants, ethnic minorities and
single mothers, as well as helping in the fight against discrimination[6]. This included
assisting the groups concerned to find work, campaigns among the general public
to discourage discrimination, diversity seminars for employers and human
resource managers and the training of employment agency staff.
In some countries, more than half of funding
went to supporting women, such as in Poland (56.5%), though in others, the
proportion was much less than half (only 39.5% in the UK). At the extreme, in Spain, it is reported that up to the end of 2011, nearly 888,000 women secured a job after
leaving co-financed programmes or 62% of those participating.
Compared to the 2000-2006 period, more funding,
EUR 1 billion overall, was allocated to helping migrants and minorities[7] to find work and
another EUR 5 billion to other measures targeted at them. In addition, EUR10
billion was allocated to general measures for disadvantaged groups, including
migrants and minorities. Up to the end of 2012, around 6.4 million people in
the two groups had participated in ESF funded programmes.

2.2.3.   Support to enhancing human
capital

There were almost 25.9 million participations in
ESF-funded measures to increase human capital up to the end of 2012.
In 13 Member States, ESF provided support for
the modernisation of education and training[8],
over EUR 8 billion being allocated to the design, introduction and
implementation of reforms. Overall, around 10% of total funding (EUR 35
billion) was allocated to education and training, while up to the end of 2010,
an estimated 5 million young people, 5.5 million people with low skills, and
576,000 older people participated in co-financed lifelong learning activities[9]. While these figures
cannot be added together because of double counting, they give indication of
the scale of the numbers involved. 
Although the figures vary according to the
characteristics of participants and the labour market situation in the country,
it is estimated that, on average, 20-35% of participants have entered
employment directly after ESF financed training. 
Reflecting the focus in some Member States on
young people, over 696,000 participants progressed into further education or
training on leaving co-financed programmes and over 262,000 cases of people
acquiring qualifications were reported. In addition, almost 236,000
participants secured employment and over 60,000 participants moved into
self-employment.

2.2.4.   Improving institutional
capacity

For the period 2007-2013, the Community Strategic Guidelines and the ESF regulation[10] identified good governance and capacity building as key issues that
needed to be addressed, especially in less developed regions and Member States.
As a result, EUR 3.7 billion of ESF funding was devoted to strengthening
institutional capacity and the efficiency of public administrations and public
services at national, regional and local level and where relevant, of the
social partners and non-governmental organisations, with a view to reforms,
better regulation and good governance. This support was organised under two
headings[11]:
·   Mechanisms for improving policy and programme design, monitoring and
evaluation at national regional and local level
·   Capacity building in the delivery of policies and programmes,
including as regards the enforcement of legislation 
Four Member States (Bulgaria, Romania, Hungary
and Greece) set up a dedicated administrative capacity building programme,
while 10 others (the Czech Republic, the three Baltic States, Poland, Slovenia,
Slovakia, Malta, Italy and the UK - in Wales) included it as a priority in one
of their programmes, mainly in regional programmes. Others, like Italy, combined the two approaches with a dedicated national programme and priority axis in
regional ones.
For example, the Bulgarian programme for
administrative capacity includes EUR 157 million of Cohesion Policy support aimed
at improving the implementation of policies and the quality of services provided
to people and businesses. It is also aimed at enhancing the professionalism,
transparency and accountability of the judiciary and improving human resource
management and the qualifications of employees in state administration, the
judiciary and civil society organisations.
The programmes are focussed on issues relating
to the structure of administrations, their human resources and the systems and
tools they use. Several success factors for effective administrative capacity
building have been identified through detailed studies:[12]:
·   the involvement of civil society;
·   a clear methodological and technical approach;
·   political commitment;
·   clear definition of responsibilities;
·   exchange of examples of good practice at EU level;
·   the use of sound monitoring and evaluation methods
 Box on EU value added through networking and the dissemination of good practice The EU provides support for mutual learning programmes in order to disseminate examples of good practice in public administration reform and to stimulate creative thinking on devising effective solutions to common problems across the EU. The European Public Administration Network (EUPAN[13]) is an informal network of the Directors General responsible for Public Administration in the Member States, the European Commission and observer countries. Its mission is to improve the performance and quality of European public authorities by developing new methods based on exchange of views, experience and examples of good practice among participants. The Commission supports a Community of Practice on Results-Based Management[14] for policy-makers and programme managers involved in the preparation, management, monitoring and evaluation of ESF programmes. A major output of the network is a source book on results-based management to guide practitioners in developing their systems in this direction. The European Public Sector Award[15] (EPSA) is aimed at recognising excellence in public authorities in the EU. The award categories have raised awareness of important aspects of public administration, so encouraging governments to modernise their administrative arrangements and practices. EPSA is not only an award but by systematically collecting examples of good practice, it has built a knowledge base of how authorities can be better organised and provide better services. In total, it has compiled and assessed over 800 such examples in the last 6 years. Under the 7th Framework Programme (FP7), the European Prize for Innovation in Public Administration was awarded to the 9 most innovative initiatives in this area, chosen from the 203 submissions received from 22 different countries, which could potentially be applied elsewhere. 

3.     Evaluation
Evidence on the impact of Cohesion Policy
3.1.      The state of play and the
challenges involved for ERDF and Cohesion Fund co-financed programmes

The figures set out above provide an indication
of the scale of activity supported by Cohesion Policy and of the kinds of
projects and measures co-financed. They also in some cases indicate the outcome
of the expenditure incurred and the results that the interventions concerned
have led to. But in themselves they do not reveal what Cohesion Policy has
achieved in terms of added-value or the difference it has made to the
development of regional or national economies, to the number of people
employed, to the quality of life of people, to a better balance of economic
activity and employment across regions or to economic, social and territorial
cohesion in general. 
This is partly because the figures are in gross
terms and some of the outcomes listed might have occurred anyway without the
financial support provided. If, for example, the ERDF, or ESF, co-finances 50%
of the cost of a particular project or measure, it may be that 50% of the
outcome should be attributed to the funding provided, more than this if the
project would not have taken place without the funding or less than this if it would
have taken place with a lower level of funding or even no public funding at
all. In the latter cases, there is, what is termed, a ‘deadweight’ element
involved, in the sense that financial support is being given to a project which
would have been undertaken anyway. This element amounts to 100% of funding if
the project or measure would have been undertaken on the same scale even in the
absence of financial support or something below 100% if it would have been
undertaken on a smaller scale. 
A further complication is that the project
might not have been undertaken without support but some other project of a
similar type would have been. For example, giving funding to an enterprise for
investment or to support jobs might mean that another enterprise does not
invest or create jobs which it otherwise would have done. In this case, the
funding provided has a displacement effect which needs to be taken into account
when assessing its outcome.
The appropriate figure to take as a measure of
the outcome of a project, or programme, and of its contribution to achieving
policy objectives can be determined only by careful evaluation of the
intervention - or set of interventions - concerned which attempts to
disentangle the effect of the financial support given from other factors at
work. This is important to do not only in order to identify what the policy
measure(s) in question achieved but also in order to assess whether the funding
involved was well spent and should continue to be used in the same way in the
future or whether the measures concerned should be modified to make them more
effective. 
For ERDF and Cohesion Fund co-financed
programmes over the period 2007-2013, at least 821 evaluations were undertaken
in Member States[16].
For the ESF co-financed programmes over the same period 721 evaluations have
been carried out in the Member States[17].
These figures are considerably more than in earlier periods. In addition, the
evaluations undertaken since 2007 have for the most part been less ‘formal’ in
nature, undertaken because of a wish to know more about how funding was being
spent rather than simply because there was an obligation under the regulations
to do so, and more directed towards building an understanding of how programmes
were working. They were also in many cases focused on particular aspects of
concern and on parts of programmes or individual measures or project types
rather than on programmes as a whole which tend to be difficult to assess,
except relatively superficially.
Most of the evaluations were not concerned
primarily with the outcome of programmes as such. Many were concerned more with
examining the processes and procedures involved in the administration of
funding, the selection of projects to support and so on, to check whether the
tasks entailed were being carried out efficiently and to identify possible
improvements. Many others were concerned largely with the progress made in
implementing programmes, with identifying any difficulties encountered in
undertaking them and to verify that they were doing what was intended. This
includes examining outcomes, though in the main on the basis of monitoring data
and the kinds of indicator considered in the previous section rather than
trying to distinguish the outcomes which could be attributed to the programme
as such.
Only just over 20% of the evaluations of ERDF
and Cohesion Fund and 23% of those of the ESF were focused on assessing the
results of programmes and their effectiveness in achieving the objectives set
when they were introduced. However, a much larger proportion (around 36%) of
ERDF and Cohesion Fund evaluations carried out in 2013 were aimed at doing so.
This increase reflects the fact that programmes by then had been running for
some time and accordingly there were more results to assess but also the
growing interest in Member States with knowing more about the effectiveness of
policies. Most of these evaluations were based to a large extent on analysing
quantitative data to try to distinguish the effect of the funding provided from
other factors influencing the outcome and to estimate the extent of any
‘deadweight’ effects. 
Another promising trend is the increasing use
of more rigorous techniques, such as counterfactual impact evaluation. This
technique is specifically designed to isolate the impact of funding by
comparing recipients of support with a ‘control’ group which did not receive
support (see Box). Although the number of evaluations using such methods was
small over the period as a whole (only around 4% of the total for ERDF and
Cohesion Fund programmes and 5% of the total for ESF programmes), it was
increasing. The increase is due partly to a series of initiatives taken by DGs
for Regional and Urban Policy and for Employment, Social Affairs and Inclusion (see
box), as well as an increasing concern among Member States to learn more about
how well measures are working and how to improve performance. 
 Counterfactual evaluations Counterfactual evaluations of interventions of the kind co-financed under Cohesion Policy essentially use the same approach as for testing new drugs or medical treatments. They involve identifying a control group which has, as near as possible, the same characteristics of the group of enterprises or individuals which receive financial support, support which can then be meaningfully compared in terms of their behaviour or performance (their profitability, for example, or their success in finding a job) with the latter. Counterfactual impact evaluations thus seek to identify net effects or impacts of interventions. The advantage of such a method is that it increases the reliability and rigour of estimates of impact. Counterfactuals are intended specifically to answer the questions ‘what would have been the situation without the intervention?’ and, more fundamentally ‘does it work?’ However, applying counterfactuals to Cohesion Policy is not a straightforward process. It requires careful selection of a valid control group, as well as collection of reliable data for both supported and control group entities and there are many cases where it is simply not technically possible to carry out. Various Commission Services are therefore actively working to make these methods as accessible as possible: ·   DG Regional and Urban Policy has launched a series of such evaluations to pilot the method and helped organise three summer schools to train evaluators and managing authorities, including for the ESF. ·   DG Employment, Social Affairs and Inclusion took stock of existing evaluations. On this basis, practical guidance was produced and two calls for proposals for pilot evaluations launched. ·   For the new programming period, both DGs have introduced requirements for the collection of relevant data. DG Regional and Urban Policy has introduced a requirement for publishing data on support to enterprises, so that third parties can access them for evaluation purposes. For privacy reasons, DG Employment, Social Affairs and Inclusion is not requiring publication of data on individuals, but has put in place requirements to record and store such data. ·   DG Employment, Social Affairs and Inclusion has set up within the Joint Research Center in Ispra, Italy, a Centre for Research on Impact Evaluation (CRIE) to support Member States with methodological advice and training. DG Regional and Urban Policy is setting up a helpdesk to provide targeted advice on selected evaluations. ·   DG Competition has drawn on experience in DG Regional and Urban Policy in drawing up evaluation requirements for the new state aids guidelines. 
The increased importance given to results in
the new programming period, as described below, will put increasing pressure on
Member States to carry out evaluations of this kind. In addition, the tight
constraints on public budgets, which are set to continue for some time to come,
already lend paramount importance to maximising the effectiveness of the way
that funding is spent. This can only be done by having more evidence about the
effectiveness of the measures supported which implies more evaluations of this
kind.
The use of counterfactual methods requires an
appropriate control group and sufficient data to compare behaviour and
performance of this group with those in receipt of funding. This is most likely
to be the case for enterprise or innovation support. It is not possible to
apply to most investment in infrastructure, though other quantitative
techniques (such as cost-benefit analysis) can be applied, while in other
policy areas (such as support for local communities), detailed case studies
provide a potential means of assessing the results of interventions. For ESF
co-financed programmes, a variety of interventions used within ESF, including
training, employment incentives and labour market services (e.g. job
counselling, coaching) would appear to be appropriate for a counterfactual evaluation,
whereas support for systems and structures seems to be more challenging in
terms of adopting a counterfactual approach.
It is equally the case that gaining a full
understanding of the effectiveness of different interventions comes not only
from applying the appropriate quantitative techniques but also from identifying
how they achieve their results, which typically requires detailed examination
on the ground of the mechanisms and processes involved.

3.2.      Evidence from evaluations of ERDF
and CF programmes

The findings of the evaluations carried out
over the period 2007-2013 are summarised below in respect of three broad policy
areas for which it is possible to draw some general conclusions on the results
of the support provided – for enterprises, RTDI and investment in transport.

3.2.1.   Enterprise support

A large number of the evaluations undertaken
during the period were concerned with assessing the effects of the financial
support given to enterprises in various forms, not least because a major part
of the funding from the ERDF was allocated to such measures in Competitiveness
regions in particular. The measures concerned are also to a large extent
relatively straight-forward to evaluate, so long as the necessary data are
available (typically from company registers but also from the companies
supported themselves), which unfortunately is not the case in many instances.
A number of the evaluations carried out were
based on counterfactual methods, as indicated above, the most satisfactory way
of distinguishing the effects of financial support, in the sense of
distinguishing the outcome directly attributable to the funding itself. The
main findings are:
·   in Germany, various evaluations have found that assistance to
enterprises contributes to the modernisation of industry and, accordingly,
further regional development, this being the case especially in the Eastern
regions[18];
·   in Portugal, investment grants have been found to increase
employment and the survival rate of companies[19];
·   in Italy, however, several evaluations of investment grants
concluded that while they had a significant effect in improving the performance
of SMEs in most cases, it was difficult to detect a positive effect on large
enterprises[20];
·   in Hungary, financial support was found to increase the investment
of firms significantly but to have less effect on value-added and profits.
·   In the UK, Germany and Italy, evaluations carried out on financial
instruments concluded that these had positive effects on enterprise
performance, though so far there have been relatively few of them in relation
to the scale of funding channelled through such instruments.
On the other hand, evaluations of enterprise
support carried out in Finland[21], Slovenia[22], Poland[23] and Latvia[24] had more difficulty in detecting a significantly positive effect of
support on the performance of enterprises. Nevertheless, the summary
conclusions[25] that can be drawn from the evidence accumulated by counterfactual
evaluations is that:
·   financial support to enterprises has the effect in most cases of
increasing investment, production and employment in SMEs partly as a result of
overcoming the constraint they face on capital markets of accessing funding;
the fact, however, that the impact varies considerably between schemes suggests
that the design of support measures and the way they are implemented are
crucial.;
·   the support provided tends to have more effect in expanding output
and employment than in increasing productivity, though this may be because of
the relatively short time period over which most evaluations have analysed the
performance of the companies supported; the jobs created, however, seem to be of
relatively high quality paid at or above the firm average and long-lasting;
·   there is evidence that measures could be more cost-effective, in the
sense that the amount of funding could be scaled down without markedly reducing
the results achieved. There are also hints that the most cost-effective measure
is the cheapest – the provision of advice and guidance to businesses; it is equally
the case that financial instruments seem to be more cost-effective than
(non-repayable) grants in the sense of having positive effects on enterprise
performance, while potentially being capable of being recycled to fund
additional investment;
·   most evaluations have found that financial support has little effect
on the behaviour of large enterprises, that it does not seem to lead to any
significant improvement in performance in respect of any of the indicators
examined, and that, accordingly, there is a large ‘deadweight’ element in the
funding provided. This raises a serious question over whether it is justifiable
to subsidise large enterprises directly. A better strategy might well be to ensure
that the region – or country – concerned is an attractive place in which to do
business.

3.2.2.   Support
of RTDI

A relatively large number of evaluations have
also carried out on ERDF support for RTDI, especially in Competitiveness
regions where, along with enterprise support, it accounts for a significant
proportion of the funding provided. Virtually all of them have concluded that
the effects of intervention have been positive. This is particularly the case
as regards the counterfactual evaluations undertaken, for the most part in Italy, Finland, Germany, Spain and Hungary, which in the main relate to the 2000-2006 period.
These have generally found that the support
provided has increased the amount that the companies concerned spent on R&D
over and above what the amount of funding received (i.e. their expenditure was
not only higher than it would have been had they not received support but the
scale of the additional spending was larger than the funding). Moreover, as in
the case of enterprise support, a number of the evaluations found that the
effects on SMEs were larger than on bigger firms, in the sense that the former
tended to increase their expenditure more than the latter.
The findings, however, are more variable as
regards the effect on productivity and profits, which in this case, are
important indicators of the success of support measures. An Italian evaluation,
for example, found that while the short-term effects of subsidies to RTDI on
company performance were positive, the long-term effects were limited. On the
other hand, an evaluation carried out in Denmark on a measure implemented in
the 1990s, though not financed by the ERDF, found that the support given to
innovation consortia increased the profitability of companies receiving the
support by 12% in relation to the control group (i.e. those not receiving
support) over the 10 years following the intervention[26]. This suggests that
the form which the support of innovations takes might well affect the effects
that it has.
At the same time, a number of evaluations found
that support had positive effects on employment in R&D activities (i.e.
that it lead to more research jobs, such as in Ireland) and the development of
innovation clusters (as in Hungary). More generally, evaluations carried out in
 Germany, Italy, the UK, Portugal and Slovenia, found that support led to an
increase in the capacity of SMEs to innovate, that, in other words, the
increase in inputs (the greater effort put into R&D) produced more outputs
which potentially improved their competitiveness.
Evaluations using other methods than
counterfactual have tended to focus on other aspects of the support provided.
In both Poland and Slovakia, for example, the support measures were found to
lack strategic concentration which reduced their effects, while in Belgium, Sweden and Portugal, it was found that there was a limited ability to involve SMEs in the
measures and so the funding failed to reach them to a large extent.
Evaluations also found that in a number of
cases the agencies or centres set up to provide RTDI assistance to firms had limited
capacity to do so which again reduced the effects of the funding intervention
provided. This was the case in Italy, especially in the less developed regions
in the south of the country, though it was less so in the more developed
regions in the north. In France, an evaluation of the ‘techno-poles’ concluded
that these centres, which received ERDF co-financing, were effective in
increasing R&D activity but pointed to the need to increase their focus on
innovations with commercial application instead of on basic research.

3.2.3.   Investment
in transport

Fewer evaluations have been carried out on
support for investment in transport than on either enterprise or RTDI support.
This is especially the case for projects co-financed from the ERDF and Cohesion
Fund for the period 2007-2013 since relatively few of them have been completed
and those that have been have been in operation only for a short period – too
short to properly judge their effects. Those that were undertaken during the
2007-2013 period, for the most part on investment financed from the previous
period’s funding, have tended to assess the effects of individual projects,
such as the construction of a motorway or a railway between two points, rather
than of a network as a whole. The latter is more relevant to consider since the
projects in question are – or should be – planned as part of a transport system
rather than individually. Indeed, treating projects in isolation is likely in
most cases to lead to misleading results in terms of the effects on ultimate
economic and social objectives, insofar as these arise from the overall network
being in operation and it is difficult, if not impossible, in principle to
isolate the effects of individual parts of this. 
For example, the gains to a region of a motorway
linking, say, the main city to a city elsewhere in the country will tend to
depend on the state of connections to it and how easy it is to access it, which
will determine the traffic which it carries and the overall savings in time and
costs which it gives rise to. Its effects, therefore, cannot easily be
separated from the effects of the ‘feeder’ roads which are constructed.
Similarly, the effects of introducing a fast rail link between two cities (not
necessarily a high-speed line) will depend on the ease of getting to the
stations at the two ends of the line as well as to those in between, which will
depend on the road and rail links to them, as well as on the ease of parking
once there. Again these effects can only meaningfully be assessed in terms of
the overall system rather than simply the rail link alone. 
The evaluations which have been carried out on
transport networks rather than on individual projects have generally found that
they have had positive effects on regional development. For example: 
·   in Greece, the construction of the Athens metro was found to reduce
road traffic in the city significantly and to boost employment and tourism, as
well as reducing pollution and improving the quality of life;
·   in Lithuania, evaluation of investment in roads was also found to
increase employment in the areas concerned through reducing transport costs and
improving accessibility; 
·   in Germany and Slovenia, ERDF support for developing urban transport
in a number of cities was found to increase the competitiveness of the regions
concerned, partly by reducing the time and costs of travel and attracting
business investment.
The evaluations undertaken, however, have also
highlighted potential problems relating to the sustainability of the investment
in that it was not always the case that future maintenance costs had been
factored into the analysis when assessing the gains relative to the expenditure
involved. 
A major reason for the small number of
evaluations of networks which have been carried out is the difficulty entailed,
especially if the concern is with assessing the economic and social effects on
particular regions or countries. Many of these effects are intangible (such as
improvements in the quality of life) or extremely long-term, in the sense that
they will continue to occur over many years, or even decades, and therefore
difficult to measure or predict. It is easier, though not entirely
straight-forward, to evaluate individual projects, especially if the exercise
is limited to the more measurable and more certain aspects, such as reductions
in journey times and time saved as well as a lowering of vehicle operating
costs in the case of roads.
Although they were limited in scope in this
way, 9 of the 10 large-scale transport projects evaluated by using cost-benefit
analysis as part of the ex-post evaluation of the Cohesion Fund in the
2000-2006 period were found to yield positive net returns, in the sense that
the net present value of the gains from the projects were estimated to be
greater than the costs of construction, operation and maintenance[27]. 
The only project for which benefits fell short
of costs was the Madrid-Barcelona high-speed line, which might well be because
of it being considered in isolation of other parts of the rail network and the
effect of the completion of the network, when it occurs, on the traffic carried
by the line. When the analysis was carried out, therefore, the line was operating
at well below capacity partly because other lines feeding into it were yet to
be completed (though also because of the effects of the recession on its use).
The benefits were, therefore, depressed as a result, illustrating the
importance of adopting a wider and longer-term perspective when assessing the
effects rather than a narrow one.
A major conclusion to be drawn from the various
evaluations, as well as from other studies of investment in transport over the
years[28],
is that while a good transport network might be important for development, its
effects depend critically on what else happens in the region or country
concerned. It, therefore, needs to be seen in combination with other factors
which contribute to development, such as a well-educated work force and the
presence of innovative enterprises.

3.3.      Evidence from evaluations of ESF
programmes

The findings of the
evaluations carried out over the period 2007-2013 are summarised below
according to policy areas. 
On the issue of
measuring the impact of ESF interventions in a robust way, which genuinely
demonstrates what difference the ESF has made to the final recipients of
interventions, evaluations were generally unable to present a significant
amount of compelling evidence. Nevertheless, the effects of ESF support have
mostly been significant and sizeable in the limited number of robust evaluations
which considered some specific ESF interventions and programmes. These show,
for example, that individuals in ESF-supported interventions are more likely to
find employment than control groups. 
In broad terms,
results in relation to Increasing Adaptability, Access to Employment, and Human
Capital were felt to be good. Additionally, some examples of significant net
benefit based on robust evaluations were available. The analysis around Social
Inclusion was less conclusive. Limited evidence around results and little by
way of evaluation evidence led typically to the assessment that ESF resources
deployed for Social Inclusion were being used less coherently and with limited
effectiveness. Promoting Partnerships and Strengthening Administrative Capacity
are less common policy fields across Member States and there is also only
limited evidence on results in these fields. However, evaluations tend to be
positive about the contribution they have made to public services.

3.3.1.    Enhancing access to employment

Where robust evaluations have been conducted by
MS these show that individuals in ESF-supported interventions are more likely
to find employment than control groups. In Member States where evaluations have
compared PES activity with ESF funded additional activity for the same client
group, positive effects have been found to result from the ESF-supported
intervention packages, which are essentially providing a more intensive and
higher quality service to unemployed people. 
Notwithstanding this, job entry rates are
typically below 50% although this varies according to the period at which these
are measured following completion of a specific activity. In a number of Member
States job entry rates are typically around 1 in 3 or less.
Wage subsidies have been deployed extensively
since the global recession to incentivise employers to recruit the unemployed
and other groups with specific disadvantages, but some evaluation evidence
suggests that significant percentages of the final recipients subsequently
return to unemployment. Evaluations also suggest public works and other
temporary job creation measures have a poor record in terms of the percentages
moving on subsequently to employment. However, stronger results are evident for
training which is vocationally specific and for traineeships and work
placements.

3.3.2.   
Equality between women and
men

It was a requirement of the Regulations for the
2007-2103 period that ESF programmes should take account of the gender
perspective at all stages (in their preparation, implementation, monitoring and
evaluation). They therefore make specific reference to measures for reconciling
work and private life, increasing the participation of women in employment and
reducing gender-based segregation, including narrowing the pay gap.
There is evidence from evaluations that
increased attention has been paid to gender equality in ESF interventions and
that in a number of Member States, they have helped to push gender equality on
to the policy agenda and measures have been implemented that would not
otherwise have been funded.
Because of the mainstreaming of the issue in
programmes, however, it is difficult to estimate the funding that has gone to
supporting equality between women and men. In terms of results however, women
account for around 52% of all recipients of support, though this proportion
varies from 39% in the UK to 56.5% in Poland. Estimates of the effect on
employment are not yet widely available, but in Spain, for example, 888,000
women are reported to have gone into a job up to the end of 2011 after leaving
an ESF programme, just under 62% of all those doing so.
The gender equality measures supported by the
ESF were aimed at achieving a number of objectives[29]:
·   increasing the ability of women to compete in the labour market by
improving their skills. 
·   training women and men in occupations traditionally dominated by the
opposite sex so increasing their career prospects;
·   assisting women to become entrepreneurs as well to provide them with
care facilities to enable them to reconcile work with their family life;
·   improving the quality of care services to encourage their take-up
and to extend their opening times as well as to train the unemployed for care
jobs. 
·   combating gender stereotyping and, to a lesser extent, educational
gender segregation through support for public awareness campaigns, seminars to
trade unions, training teachers and parents and revisions to school curricula;
·   aiding poverty-stricken, vulnerable women, often suffering from
multiple discrimination as well as victims of violence to help them gain
skills, confidence and so economic independence.
There is evidence, in general, that the
multi-dimensional strategies combining different types of intervention are
becoming more important to tackle the multiple causes of discrimination or the
different reasons for gender gaps. Examples include combining personal guidance
or classroom teaching of practical daily skills, facilitating access to psychological
support, language lessons, vocational training and help over job search, which
is likely to be more effective than providing these measures in isolation.
At the same time, there have been significantly
fewer measures aimed at influencing the social, economic or institutional
context or targeted at the demand side, such as training employers or human
resource managers or giving incentives to firms to employ women as managers.
The evaluation carried out emphasised that there was a need to intensify such
measures in order to tackle the root causes of discrimination.

3.3.3.   Social inclusion - migrants and minorities

A general finding
from MS evaluations is that the most effective ESF supported services are those
which are designed very specifically around the needs of particular groups,
with training appearing as a very effective measure for migrants. In relation
to the results for different groups, there is very limited evidence. 
More ESF support was provided to increase the
labour market involvement and social inclusion of migrants and ethnic
minorities in the 2007-2013 period than in the previous one. Some EUR 1.17
billion of funding was allocated to specific measures to help migrants and a
further EUR 10 billion to general measures targeted at disadvantaged groups,
including migrants and minorities, half of this being estimated to go on the
latter. In total, therefore, just over 8% of the overall ESF budget was
allocated to support for this group.
Around 1.2 million of the people concerned are
reported to have participated in ESF co-financed measures up to the end of 2012
(862,000 of them migrants), though the actual figure may be some 100,000 higher
because of the under-reporting of ethnic minorities, especially Roma. 
An evaluation of ESF support[30] found that it helped
people to find employment by strengthening their employability, especially
their ICT and basic literacy and communication skills, as well as by
encouraging them to become self-employed
ESF support was also found to have helped to
improve initial integration services, to create new networks and organisational
structures and generally to improve the capacity of public bodies to assist
people with a minority background. At the same time, knowledge has been gained
and experience shared between public bodies and NGOs with a specialist
understanding of the needs of migrants and ethnic minorities and the barriers
they face in accessing the labour market.
While there are many specific measures for
Roma, an ‘explicit but not exclusive’ approach has increasingly been adopted
towards them so as to avoid separating them completely from other groups, which
would run the risk of them becoming even further segregated. Integrating
measures together seems to be most effective, linking support for education and
training with access to housing, transport and health services and improvements
in basic infrastructure, which are basic pre-conditions for Roma being able to
find employment. 
The evaluation identified a number of examples
of good practice, such as in Spain, where NGOs were consulted early and
remained closely involved, along with final recipients themselves, in the
implementation of the measure. 
Examples of counterfactual ESF impact evaluations
carried out in Member States
An evaluation of the 2007-13 ESF Programme for England[31],
assessed the effects of interventions aimed at increasing the employability of
recipients of Jobseekers Allowance (payable for up to 6 months) and Incapacity
Benefit or the Employment and Support Allowance (payable typically to the
longer-term unemployed) on the basis of administrative data. The large number
of people covered made it possible to carry out detailed statistical analysis,
distinguishing recipients in terms of their characteristics and type of support
received. The evaluation found consistently positive effects in increasing
access to employment which were larger for the more disadvantaged group.
An evaluation of social integration programmes targeted at people
with disabilities and ex-offenders in Lithuania[32] was carried
out to assess their effects in re-integrating participants into the labour
market. The data used enabled those eligible for the programmes who did not
participate to be identified as well as those that did. It found that the
programmes increased the probability of participants finding employment, the
duration of this and the earnings received. It also found that the effects on
those with disabilities were greater than on ex-offenders[33]. 

4.     The modelled impact of Cohesion Policy 2000-2006 and 2007-2013 

The only way of obtaining a complete
overview of the impact of Cohesion Policy on the EU economies is by means of a
macroeconomic model which incorporates the available evidence on the effects of
the various kinds on interventions. 
This section reports on a model-based[34] assessment of the potential impact of the Structural Funds and the
Cohesion Fund during the previous programming periods 2000-2006 and 2007-2013
in the Member States which were the most important recipients of financial
support. These are the three EU-15 Cohesion countries, Portugal, Spain and Greece,
which received funds over the two programming periods as a whole, together with
Ireland, which was a recipient of the Cohesion Fund up to 2003, and the EU-12 Member
States which received pre-accession assistance from 2001 and saw a major
increase in funding after accession in 2004 or 2007 in the case of Bulgaria and
Romania. They also include the eastern part of Germany and the southern Italian
regions (the Mezzogiorno). (Note that a more detailed description of the
macroeconomic model used to generate these estimates is set out in the next
Chapter in relation to estimating the effects of Cohesion Policy funding in the
present programming period which involves the same methodology – i.e. comparing
developments without the funding with those with the investment which it
finances.) 
In the programming period 2000-2006, more
than EUR 250 billion was spent on Cohesion Policy in the EU-15 and on
pre-accession aid and structural interventions in the EU-10. Spending in the Member States listed above amounted
to EUR 186 billion.
For the programming period 2007-2013, the total
budget is EUR 336 billion, of which EUR 173.9 billion is allocated to the
Member States that have entered the EU since 200, EUR 76 billion to Spain, Greece and Portugal and EUR 26 billion to the Eastern German Lander and the Mezziogiorno in Italy. 
Figures 86 and 87 show the potential impact
of Cohesion Policy on GDP (‘potential’ in the sense of what it is estimated to
be if the effects of funding are as assumed in the model) for the two
programming periods respectively, showing in each case the average short-run
impact on the one hand and the longer run impact, on the other. 
Figure 1: Estimated impact of Cohesion Policy
2000-2006 on GDP
Figure
2 Estimated impact of
Cohesion Policy 2007-2013 on GDP
These results show an unambiguously positive
impact of Cohesion Policy on GDP in the Member States considered. The results
of the model simulation suggest that the investment
financed under Cohesion Policy during the period 2000-2009 has the potential to
have increased GDP on average by up to 1.8% a year in Latvia relative to the
baseline (i.e. as compared with the level of GDP in the absence of this
investment), by up to 1.6% a year in Portugal and 1.3% a year in Greece
(Figure 88). Cohesion policy programmes are also expected to improve the
conditions of the labour market. Over the same period, the simulation suggests
that 2000-2006 programmes increased employment by around 0.5% as compared to
baseline in Lithuania and Portugal, and by 0.3% in Poland, Latvia and Spain. 
Over the period 2007-2016, the average increase
in GDP as a result of Cohesion Policy is estimated to amount to 2.1% a year in Latvia, 1.8% a year in Lithuania and 1.7% a year in Poland as compared with the baseline projection.
In terms of employment, the average annual impact is estimated at 1% in Poland, 0.6% in Hungary, and 0.4% in Slovakia and Lithuania. 
For both periods, the impact in the medium and
longer-term for all countries exceeds the impact during the funding period
itself. In 2015, the effect of the funding going into investment in the
2000-2009 period is to increase GDP in Spain by almost 1 percentage point more
than during the period itself (by 1.9% instead of just under 1%) and in both
Greece and Portugal, by over 1 percentage point (Figure 88), pushing the
increase up to around 3% a year relative to the baseline in both countries. The
impact on employment also increases in time. In 2014, it reaches 1.3% in Lithuania, 0.9% in Latvia and 0.8% in Poland.
The longer-term effect of funding for the
2007-2016 programming period is even more pronounced, the increase in GDP in
2022 as a result of the additional investment carried out being more than
double that of the average increase during the period. In both Lithuania and Poland, therefore, in 2022, GDP is raised by over 4% above what it would be without
the investment concerned and in Latvia by 5%. For the same year, employment is
increased by 1.8% in Poland and by 0.7% in Hungary and Slovakia. 
The results of these simulations highlight the
fact that the estimated gains from expenditure under Cohesion Policy build up
over the years as a result of the strengthening of the competitiveness of the
economies receiving support and continue well after the investment programmes
concerned come to an end. During the funding period itself, therefore, most of the
effect on GDP comes from the increase in demand which the expenditure gives
rise to, which is assumed to be partly crowded out as a result of the increases
in interest rates, wages and prices which follow from this. In the longer-run,
the effect of the investment in increasing productivity becomes stronger,
leading to an increase in the potential output of economies, or their capacity
to sustain growth, which means that GDP can grow without this generating
inflationary pressure. 
Assuming that the effects of the added
investment brought about by the funding provided are as the evidence seems to
indicate, the simulations, therefore, demonstrate that the strengthening of the
productive potential in the economies receiving support is both long-lasting
and larger in scale than the short-term effects of the stimulus to demand from
the injection of finance.
The Impact of
Cohesion Policy: a summary of the economic research carried out 
There are a great many research papers which have been produced since
the mid-1990s which use econometric techniques to assess the effects of Cohesion
Policy on the growth of regions and the extent of convergence of GDP per head
towards the EU average. Most of them focus primarily on the earlier programming
periods and on the effects of the policy on regions in the EU-15 and only a few
of the most recent ones cover the EU-12 countries as well. The papers use a
range of different techniques to generate estimates of the effects of policy as
distinct from the many other factors at work.
Around half of the studies which have been carried out have found
significantly positive effects of Cohesion Policy on EU growth[35], while a quarter or so
have found positive effects but less strong and not in all cases. This leaves
around a quarter of the studies which have found either little effect or
effects that were not statistically significant. Many of these studies,
however, were published between 1996 and 2004 when there were more limited data
available covering a shorter time span.
The great majority of the studies published since 2005, which are based
on larger set of data covering a longer time period have found that the policy
has had broadly positive results[36].
This is equally the case for studies covering EU-12 countries as well as the
EU-15. 
Nevertheless, while most studies find that Cohesion Policy has helped
to reduce regional disparities in economic performance, they also conclude that
the effects are not uniform[37]
and that many different factors influence whether or not the policy is
successful in a particular context as well as the scale of the effect. These
factors relate, in particular, to the institutions in place and the efficiency
of governance, the national policies pursued and the performance of
neighbouring regions[38]
Equally, there is recent evidence that the performance of the policy is
affected by the way funding is distributed and allocated between policy areas,
an issue which is central to the recent reforms. 

5.     Conclusion

Assessing the impact of cohesion policy is not
an easy task. However, the progress achieved as a result of the policy are
constantly monitored while the effects have been evaluated at various levels
using many different methods. They generally confirm the tangible and concrete
benefits that Cohesion Policy has produced and continues to produce in EU
regions and cities.
The policy has led to numerous achievements.
Thousands of projects have provided support for investment in SMEs or helped to
start operations. Other projects have contributed to improving the capacity of
the business sector to transform R&D into valuable innovation. Cohesion
Policy has made it possible for millions of households and firms to connect to the
most advanced ICT networks. It has financed the construction of kilometres of
roads and railways, so improving transport links in areas of the EU where their
absence or poor state has hindered economic development. Cohesion Policy has also
contributed to improving access to the labour market across the EU and has helped
to better integrate vulnerable social groups into society. It has equally worked
to protect the environment, notably by co-financing the installation of
environmental infrastructure in places where it would otherwise not have occurred
because of lack of resources. 
These achievements have helped to improve the
structure of the EU economies while at the same time promoting an inclusive and
sustainable pattern of development across the EU. Cohesion Policy support has significantly
enhanced the performance of enterprises, especially of SMEs, and increased
their investment and employment, as well as the R&D they undertake and
their capacity to innovate. Investment in transport infrastructure, when carried
out as part of a coherent strategy, has been shown to have a positive effect on
regional development.
The changes brought about by Cohesion Policy at
the micro level show up after a time at the macro level. Assessing the impact
of policy on GDP growth and employment requires account to be taken of both
direct and indirect effects of interventions, which can only be done through simulating
policy using macroeconomic models. Such simulations suggest that Cohesion
Policy significantly contributes to increasing GDP and employment, in
particular in the Member States which are the main recipients of financial
support. The models also show that, in line with the long-term objectives of policy
to permanently increase the productive potential of EU economies, the effect continues
to build up years after the programmes have ended. 
Even if the
evaluations indicate that positive results have been achieved by Cohesion
Policy, there is still room for improvement. In particular, the evidence
underlines the importance of concentrating funding on a limited number of key
priorities and ensuring that the right conditions are in place for policy to
have its maximum impact. The design and implementation of the policy itself
could also be enhanced by focusing more on results, setting coherent objectives
and selecting clear and appropriate targets for programmes. To a large extent,
these are the aims which have driven the reform underlying the 2014-2020
programmes.
[1]
      ESF Expert Evaluation
Network, 2014, Final Synthesis Report: Main ESF achievements, 2007-2013,
Metis and University of Glasgow
[2]
      Although some experts argue that targets were not particularly ambitious,
this needs to be balanced against the serious deterioration in the labour
market situation in relation to when the targets were set.
[3]     ESF
Expert Evaluation Network, 2013,  Final Synthesis Report on Women and Young
People, Metis and University of Glasgow.
[4]
      Final Synthesis Report on Social Inclusion, ESF Expert Evaluation
Network, Metis and University of Glasgow, December 2012
[5]
      This includes several reporting categories under the ESF relating to
social inclusion.
[6]
      Evaluation of the European Social Fund’s support to Gender Equality, GHK
and FGB, January 2011
[7]
      CSES, 2011, Evaluation of ESF Support for Enhancing Access to the
Labour Market and the Social Inclusion of Migrants and Ethnic Minorities.
[8]
      Evaluation of ESF Support for Enhancing Access to the Labour Market and
the Social Inclusion of Migrants and Ethnic Minorities, CSES, May 2011
[9]
       Ecorys, 2012, Evaluation of the ESF support to Lifelong Learning.

[10]     Article 3.2(b) – Regulation EC
1081/2006
[11]     European Commission, 2013, Cohesion Policy: Strategic Report
2013. Factsheet: Institutional capacity building.
[12]     Ecorys 2011
[13] http://www.eupan.eu/ 
[14] For more information: http://www.coprbm.eu/?q=node/1
[15] http://epsa2013.eu/
[16]     This is the estimate made from the details of evaluations
carried out in their countries by the Network of Independent Evaluation Experts
set up by DG Regional Policy in 2010 to monitor the performance of ERDF and
Cohesion Fund programmes over the 2007-2013 period in each of the 27 Member
States and to collect information on evaluation activity. Some of the
evaluations were financed from funding from the 2000-2006 period (which came to
an end only in December 2009. See …
[17]     As identified by the ESF Expert Evaluation Network at the end
of 2013.
[18]     See: F.-J. Bade, Prognos AG und NIW - Niedersächsisches Institut für
Wirtschaftsforschung. 2010. Endbericht zum Gutachten Erfolgskontrolle der
einzelbetrieblichen Förderung von Unternehmen aus der GRW und dem EFRE in den
Jahren 1998-2008: Wachstums- und Beschäftigungswirkungen für Niedersachsen.
GEFRA und IAB (2010), Ex post evaluation of Cohesion Policy programmes
2000-2006 financed by the European Regional Development Fund; Work Package 6c:
Enterprise Support - an exploratory study using counterfactual methods on
available data from Germany, Münster, Nürnberg. Prognos AG. 2011a. Stand und
Perspektiven der EFRE Förderung in Bayern - Zwischenevaluation des
Operationellen Programms des EFRE im Ziel RWB Bayern 2007-2013.
[19]     Counterfactual analysis of the impacts of support schemes
to businesses in POE/PRIME 2000-2006 (May 2013)
[20]     Among several evaluations
see for instance: ERDF OP Campania Ex post evaluation of of aid schemes for
enterprises 2000-2006; ERDF OP Sicily Evaluation of supporting enterprise
policy; M. Mariani, F. Mealli, E. Pirani Gli effetti dei programmi di aiuti
rimborsabili sulla crescita e la sopravvivenza delle PMI. Un disegno valutativo
longitudinale applicato al caso della Toscana. 2012 IRPET; D.Bondonio, A.
Martini Counterfactual Impact Evaluation Of Cohesion Policy: Impact And
Cost-Effectiveness of Investment Subsidies In Italy. 2012.
DG Regio.
[21]     Pietarinen M., 2012, Yritystukiselvitys (An investigation on
enterprise support). Ministry of Labour and the
Economy. Innovation 7/2012. 
[22]     Evaluation of measures for
promoting entrepreneurship and competitiveness in Slovenia in the period
2004-2009 (2012).
[23]     Evaluation of direct and
indirect support to the SME sector in ROP and a recommendations on the support
of SMEs in the future financial perspective 2014-2020 (2013).
[24]     Evaluation of
the impact of entrepreneurship and innovation support programmes and
recommendations for improving the support system (April 2013)
[25] For a summary of the evidence see Mouqué, 2012, What are
counterfactual impact evaluations teaching us about enterprise and innovation
support?, http://ec.europa.eu/regional_policy/sources/docgener/focus/2012_02_counterfactual.pdf
[26] ‘   An analysis of firm growth effects of the Danish Innovation
Consortia scheme’, Centre for Economic and Business Research, Denmark.
[27]     The 10 projects were the high-speed railway line between Madrid
and Barcelona; the railway line between Lisbon and the Algarve in Portugal;
Thriassio-Pedio-Eleusina-Korinthos railway in Greece; the upgrading of the
Bratislava Rača–Trnava railway line in Slovakia; the A2 motorway in Poland
between Konin and Strykow; a 75 km stretch of the A23 motorway in Spain running
from Pau in France to Zaragoza; the Agiou Konstantinou bypass in Greece; the M!
motorway in Ireland; the IX B corridor in Lithuania, including the Vilnius southern bypass; and the eastern section of the M0 Budapest ring road in Hungary.
[28]     For example: OECD, 2011, Building resilient regions for
stronger economies, Regional Outlook 2011 and Ricardo
Crescenzi and Andres Rodriguez-Pose, 2012, Infrastructure and Regional
Growth in the European Union, CEPR Discussion Paper Series no 8882
[29]As indicated by an evaluation of such measures at:
http://ec.europa.eu/social/keyDocuments.jsp?pager.offset=10&langId=en&mode=advancedSubmit&policyArea=0&subCategory=0&year=0&country=0&type=0&advSearchKey=evaluationesf

[30]http://ec.europa.eu/social/keyDocuments.jsp?type=0&policyArea=0&subCategory=0&country=0&year=0&advSearchKey=evaluationsocialinclusion&mode=advancedSubmit&langId=en&orderBy=docOrder 
[31]     http://research.dwp.gov.uk/asd/asd5/ih2011-2012/ihr3.pdf

[32]     The interventions under evaluation were financed under the
2004-2006 programming period. However, the data used for the analysis expanded
until 2010 and the study provided recommendations on how the use of the EU
structural assistance might be improved during the rest of the programming
period 2007-2013.
[33]     Public Policy and Management Institute, 2012, Evaluation of
social integration services for socially vulnerable and socially excluded
individuals for the effective use of the EU structural assistance for the
period of 2007-2013
[34]     The model used to
carry out this impact assessment is an extension of Quest III containing a
representation of the effect of investment in human capital and endogenous
technological change, which makes it particularly suitable for the evaluation
of Cohesion
Policy type of structural interventions. It also includes explicit cross-country linkages through bilateral trade relationships
to capture spill-over effects and the interaction between EU Member States. For a more detailed description of the model, see Varga, J.
and in 't Veld,J.,2011, A
model-based analysis of the impact of Cohesion Policy expenditure 2000–06:
Simulations with the QUEST III endogenous R&D model, Economic Modelling 28 (2011) 647–663.
[35]       Bradley, J.,
Untiedt, G., and Mitze, T., 2007, Analysis of the Impact of Cohesion Policy:
A Note Explaining the HERMIN-Based Simulations, Technical Note,  Cappellen,
A., Castellacci, F., Fagerberg, J., and Verspagen, B., 2003, The Impact of
EU Regional Support on Growth and Convergence in the European Union,
Journal of Common Market Studies, 41, 621-644 , De la Fuente, A., and Vives,
X., 1995, Infrastructure and education as Instruments of Regional Policy:
Evidence from Spain, Economic Policy, 10.20, 13-51, Martin, R., and Tyler,
P., 2006, Evaluating the Impact of the Structural Funds on Objective 1
Regions: An Exploratory Analysis, Regional Studies, 40.2, 201-210
[36]       Midelfart-Knarvik,
K.H., and Overman, H.G., 2002, Delocation and European Integration – is
Structural Spending Justfified?, Economic Policy, 17, 323-359,  Ederveen,
S., de Groot, H.L.F., Nahuis, R., 2006, Fertile Soil for Structural Funds? A
Panel Data Analysis of the Conditional Effectiveness of European Cohesion Policy,
Kyklos, 59, 17-42 , Hagen, T., and Mohl, P., 2009, Econometric Evaluation of
EU Cohesion Policy: A Survey, Discussion Paper 09-052, ZEW, Mannheim
[37]       De
Freitas, M.L., Pereira, F., and Torres, F., 2003, Convergence among EU
Regions 1990-2001: Quality of National Institutions and ‘Objective 1’ Status,
Intereconomics, 38.5, 270-275,  Garcilazo, E., and Rodriguez-Pose, A., 2013, Quality
of Government and the Returns of Investment: Examining the Impact of Cohesion
Expenditure in the European Regions, OECD Regional Development Working
Papers, No 2013/12, Paris 
[38]       Becker,
S.O, Egger, P.H, and von Ehrlich, M., 2012a, Too Much of a Good Thing? On
the Growth Effects of the EU's Regional Policy, European Economic Review,
56, 648-668,  Ederveen, S., Gorter, J., de Mooij, R., and Nahuis, R., 2002, Funds
and Games: The Economics of European Cohesion Policy, CRB and Koninklijke
De Swart, Amsterdam. See: http://www.enepri.org/files/CPBstudy.pdf,  Bouvet, F., and Dall’erba,
S., 2010, European Regional Structural Funds: How Large is the Influence of
Politics on the Allocation Process, Journal of Common Market Studies, 48.3,
501-528
Chapter 8: Cohesion Policy in 2014-2020

1.     KEY ELEMENTS OF THE REFORM 

A two-year negotiation on the reform of
Cohesion Policy was concluded in December 2013. As a result, the Policy will
invest around a third of the EU budget in key areas in line with the Europe
2020 strategy of smart, sustainable and inclusive growth. To this end, 11
thematic objectives corresponding to the Europe 2020 priorities have been
defined in the new legal framework. To maximise the impact of investment, Member States and regions need to concentrate EU funding on a limited number of these
objectives in the light of the specific territorial challenges they face and
their development needs. 
Ensuring a greater focus on the results of
EU-supported investment by better indicators, reporting and evaluation is at
the core of the reform. To improve performance, new conditionality provisions
have been introduced to ensure that the necessary framework conditions for
effective investment are in place and that the impact of cohesion funding is
not undermined by an unsound macroeconomic framework. 
Common provisions have been established for
all EU funds supporting economic and social development (i.e. the ERDF, ESF,
Cohesion Fund, EAFRD and EMFF) to improve coordination and harmonise the implementation
of what are now termed the European Structural and Investment (ESI) Funds. This
should also simplify their use by recipients and reduce the potential risk of
irregularities. 
More effective coordination between the ESI
funds and other EU policies and instruments (such as the relevant
country-specific recommendations under the European Semester, Horizon 2020, the
Connecting Europe Facility and the Competitiveness of Enterprises and SMEs
programme) is another important element of the reform and the Common Strategic
Framework (CSF) is intended to provide guidance on how to achieve this. 
To draw on EU funding, each Member State has to prepare a Partnership Agreement setting out its investment priorities
and how they contribute to responding to the relevant country-specific
recommendations under the European Semester and to reaching the Europe 2020
objectives, as well as the arrangements for managing the funds effectively. The
procedures for programming, management, monitoring and control then need to be
described in more detail in national or regional programmes.
To strengthen ‘ownership’ of the programmes
on the ground, a new European code of conduct lays down the main principles of
how Member States and regions should organise partnerships and gives guidance
on how best to do this.
The new legislative and policy framework encourages
further expansion and strengthening of the use of financial instruments as a
more efficient and sustainable alternative to traditional grant-based financing
in a number of areas. In addition, a number of new ways of implementing policy
have been developed to tackle particular territorial development challenges,
such as Integrated Territorial Investments (ITI), community-led local
development (CLLD) and multi-fund programmes combining finance from the ESF,
ERDF and the Cohesion Fund.

1.1.      New geography and funding

Cohesion Policy provides financial support to
help regions to overcome the obstacles to their development, whether these take
the form of inadequate infrastructure or lack of capacity to innovate or to
adapt to a changing global economic environment. These obstacles are present in
all regions to varying degrees, though the level of financial support provided
reflects their level of development and their need for financial assistance to
tackle them effectively. 
In the 2014-20 period, Cohesion policy funding
will be directed towards two main goals: Investment for growth and jobs and
European territorial cooperation. For the Investment for growth and jobs goal,
EU funding will be concentrated (EUR 182.2 billion out of a total of EUR 351.8
billion at current prices) on the less developed regions with a GDP per head of
less than 75% of the EU average, on 71 NUTS 2 regions with a population of some
128 million (i.e. 25% of the EU total), mainly located in the eastern and
southern Member States (see Map 1).
In order to support regions no longer
qualifying for support under the Convergence Objective, which could be
adversely affected by the sudden reduction in EU funding, and all other regions
with GDP per head above 75% of the EU average but below 90% of the average, a
new category of Transition regions has been established. This covers 51 NUTS 2
regions mainly located in central Europe with 68 million inhabitants
representing 14% of the EU population which together receive some EUR 35.4
billion of funding.
All other regions with a GDP per head of more
than 90% of the EU average (151 regions with 307 million people or 61% of the
total in the EU) will be part of a category of ‘more developed’ regions. These
are mainly located in the central and northern EU Member States and receive EUR
54.4 billion. 
The Cohesion Fund will continue to provide
support to Member States with GNI per head of less than 90% of the EU average
and to co-finance investment in environmental infrastructure and the
trans-European transport networks. 14 Member States located in eastern and
southern Europe, as well as Cyprus on a transitional basis, are eligible for
support (Map 84) amounting to EUR 74.7 billion, of which EUR 11.3 billion is to
be transferred to the Connecting Europe Facility[1].
 Box 1: The Connecting Europe Facility (CEF) The Connecting Europe Facility is a new funding instrument for transport, energy and telecommunication trans-European networks (TENs) with a budget of EUR 33 billion. The largest share – EUR 26 billion – will go to transport, while energy and telecommunications will receive EUR 5 billion and EUR 1 billion, respectively. Additional investment from private and public sources will be leveraged through the use of innovative financial instruments, such as project bonds, and these could be extended after 2016 if the evaluation of the initial phase is positive. Investment in transport is focused on the European core network which is to be completed by 2030 as a priority, while a comprehensive network is to be completed by 2050. Projects of common interest will be carried out in cross-border areas where transport links are missing, in areas where infrastructure is lacking, and where connections between different modes of transport are inadequate and to establish interoperability. Projects are also intended to reduce greenhouse gas emissions from transport. Priority will be given to multi-modal transport corridors and ‘motorways of the sea’. In the case of energy, the CEF will co-finance key infrastructure projects and those of common interest in order to create a power grid which can absorb the increasing amount of renewable energy required to reduce greenhouse gas emissions. A project can be of common interest if it involves at least two Member States, increases market integration and competition in the energy sector as well as security of supply, and contributes to meeting EU environmental and energy objectives. In the case of telecommunications, the CEF will provide seed capital and technical assistance for projects to provide broadband networks and services. Most of the funding will support the provision of seamless cross-border public services such as e-Procurement, e-Health and Open Data. A minor part will be used for broadband projects in collaboration with the European Investment Bank (EIB). To be eligible, projects will need to incorporate state-of-the-art technology combined with either innovative business models or those which can be easily replicated. 
In order to take account of the
differential effect of the crisis on Member States and regions, a mid-term
review of the allocation of funding between them is planned in 2016 on the
basis of the then available statistics. Any modifications in the allocation
will then be spread over the years 2017-20. 
To ensure that the principle of
co-financing is respected but that national contributions are set at an
appropriate level, maximum rates of EU co-financing have been fixed according
to the level of economic development of the regions or Member States concerned.
As regards the Structural Funds, these rates vary from 50% in the more
developed regions to 85% in the less developed ones (Map 86).
 Box : The European Union Solidarity Fund (EUSF) The European Union Solidarity Fund (EUSF) was set up in the wake of the severe floods in Central Europe in the summer of 2002 to assist regions in both EU Member States and accession countries hit by major natural disasters which have serious effects on living conditions, the natural environment or the economy. A natural disaster is regarded as ‘major’ if it causes damage in excess of a particular level of costs, which is specified for each country, or if it affects the majority of the population in a region and is considered to have serious and lasting consequences for economic stability and living conditions there. The EUSF helps to finance emergency operations, such as the restoration of essential infrastructure; the provision of temporary accommodation and the cost of emergency services to meet the immediate needs of the population as well as of preventative measures, such as the construction of dams or dykes, to stop the situation from becoming worse. Since 2002, the Fund has provided support totalling EUR 3.6 billion to help those affected by 56 disasters, including floods, forest fires, earthquakes, storms and droughts, in 23 Member States. For the 2014-2020 period, Solidarity Fund aid can be mobilised up to a maximum annual total of € 500 million. New rules have been introduced to facilitate faster and simpler access, such as the provision of advance payments on request, to allow for quicker reaction and presence in the areas struck by disasters and to encourage Member States to implement more effective risk prevention measures. Eligibility for support has also been clarified, particularly in the case of regional disasters. A particular focus is put on minimising the risks of disaster and investing in prevention. The benefits of this approach have been demonstrated frequently – most recently, by the floods in central Europe in 2013 which were larger in extent than those 12 years ago, but caused far less loss of life and damage thanks to the preventive measures taken. According to the World Bank, one Euro invested in prevention on average saves between 4 and 7 Euros in damage. In the 2007-2013 period, more than EUR 5 billion was invested under the Cohesion Policy in risk prevention and for 2014-2020, it is among the thematic objectives of Cohesion Policy. In addition, a ‘floods’ Directive is to be implemented and disaster management legislation is to be revised, including better risk monitoring and closer cooperation on both prevention and response. 
 Map 1 Structural Funds (ERDS and ESF) eligibility 2014-2020 || Map 2 Cohesion Fund eligibility 2014-2020 
Map 3 Investment for growth and jobs goal:
maximum co-financing rate for Structural Funds support, 2014-2020

1.2.      Thematic concentration in support of Europe 2020

In the 2014-20 period, Member States and regions need to concentrate financial resources on a limited number of policy areas
which contribute to the pursuit of Europe 2020 strategy in order to maximise
the impact of EU investment. This is a response to the experience of earlier
periods, which showed that the impact of EU funding was more limited than
expected due to resources being too widely spread. 
This was due in large part to the broad scope
of priorities from which Member States could select, but also to their
reluctance to concentrate resources on a small number of priorities where they
could have a significant impact. While the introduction of ‘earmarking’,
requiring that a certain proportion of funding was allocated to the Lisbon
priorities to ensure greater focus on common EU policy objectives was a step
forward in 2007-13, the results have been mixed.
Two requirements for ‘thematic’ concentration
have been introduced for 2014-20. First, EU funds have to be focused on key
areas which are line with the Europe 2020 strategy for smart, sustainable and
inclusive growth and, more particularly, with the country specific
recommendations issued by Council in the context of the European Semester.
Secondly, fund-specific regulations stipulate how much funding should be
allocated to certain objectives.

1.2.1.   Targeting
resources at key areas of growth

Investment financed by the ERDF has to be
concentrated on four key priorities: R&D and innovation, the digital
agenda, support for SMEs and the low-carbon economy. The minimum level of
funding to be allocated to these is differentiated according to the level of
development of the region concerned. In more developed regions, it is at least
80%, in transition regions, 60% and in less developed regions, 50%. In
addition, within these amounts, at least 20% has to be allocated to a low
carbon economy in more developed regions, 15% in transition regions and 12% in
less developed regions (Maps 87 and 88). 
In the case of the ESF, allocations have to be concentrated
on up to five investment priorities under the relevant thematic objectives
relating to employment, social inclusion, education and institutional capacity
building. This should help to achieve more from the funding provided across the
EU. It should also ensure a clearer link with the European Employment Strategy
and the Integrated Guidelines on Employment. 
Regions and Member States will have to make
clear choices on their objectives and the concentration on a limited number of
these should enable a critical mass of resources to be reached, ensuring a
meaningful impact on the areas concerned in terms of growth and jobs. 
 Map 4 Funding for R&D&I, competitiveness of SMEs and the low carbon economy, 2014-2020 || Map 5 Funding for the low-carbon economy, 2014-2020 

1.2.2.   Promoting
employment, education and social inclusion

In order to promote employment, education and
social inclusion throughout Europe, the ESF will receive at least EUR 80
billion, slightly up in money terms on the 2007-2013 amount. The shares
allocated to each Member State have been determined in terms of a proportion of
the combined ESF and ERDF support which it is considered that they should
receive under the Investment for Growth and Jobs goal (see Table 31). These
shares reflect the differing investment needs of Member States which are partly
determined by their level of development. In general, less developed Member
States have a wide range of infrastructure investment needs, including, for
example, improved transport links, whereas for more developed ones, there is
more of a need for investment in human capital. 
Within the ESF allocation, at least 20% has to
go to furthering social inclusion and combating poverty and discrimination.
Table 31: ESF minimum shares per Member State of ESF and ERDF support under the Investment for Growth and Jobs goal
 ESF minimum share ||   || ESF minimum share 
 (% of ERDF/ESF) || (% of ERDF/ESF) 
 Belgium || 52,0% ||   || Lithuania || 24,2% 
 Bulgaria || 28,7% ||   || Luxembourg || 50,7% 
 Czech Republic || 22,1% ||   || Hungary || 24,0% 
 Denmark || 50,0% ||   || Malta || 21,6% 
 Germany || 36,8% ||   || Netherlands || 50,0% 
 Estonia || 18,0% ||   || Austria || 43,5% 
 Ireland || 51,7% ||   || Poland || 24,0% 
 Greece || 28,1% ||   || Portugal || 38,5% 
 Spain || 27,7% ||   || Romania || 30,8% 
 France || 41,7% ||   || Slovenia || 29,3% 
 Croatia || 24,6% ||   || Slovak Republic || 20,9% 
 Italy || 26,5% ||   || Finland || 39,5% 
 Cyprus || 30,7% ||   || Sweden || 42,5% 
 Latvia || 20,7% ||   || United Kingdom || 45,9% 
Given the urgent priority of tackling high
levels of youth unemployment in many Member States, a new Youth Employment
Initiative co-financed by the ESF has been launched to help young people into
employment or to receive the education and training necessary to improve their
chances of finding a job. The measures included involve support for
apprenticeships, self-employment and business start-ups as well as for work
experience and for continued education and training. Regions eligible for
support under the Initiative are those with youth unemployment rates of more
than 25% in 2012 and those with rates of over 20% which are in countries where
the rate increased by more than 30% in 2012 (see: Map 89).
EUR 6.4 billion has been allocated to the
Initiative, at least EUR 3.2 billion of which comes from targeted investment
from the ESF national allocations and the remainder from a specific EU budget
line. These amounts could be increased following the mid-term review of the EU
budget in 2016. 
Map 6 Youth employment initiative, 2014-2020

1.3.      Strengthening the effectiveness of investment

The effectiveness of Cohesion Policy funding
depends on sound macroeconomic policies, a favourable business environment and
a strong institutional framework. In many sectors, a combination of strategic
and regulatory conditions and public investment is necessary to tackle
bottlenecks to growth effectively. 
Studies, however, suggest that inappropriate
policies as well as administrative and institutional constraints have limited
the effectiveness of EU funding in the past. Gaps also remain as regards the
implementation of EU legislation into national law in areas directly linked to
Cohesion Policy. Although there were attempts in the past to establish
‘conditionalities’ linked to the strategic, institutional and administrative arrangements
in place, their application remained discretionary and unsystematic.
Ex-ante
conditionalities have therefore been introduced in the 2014-20 period to ensure
that the effectiveness of EU investment is not undermined by unsound policies
or regulatory, administrative or institutional bottlenecks. These
conditionalities are limited in number and focus on the framework conditions
that are perceived as being most relevant for investment. They are built on
existing obligations that Member States have to comply with, so avoiding adding
to these or going beyond requirements which already exist. 
There are two types of ex-ante
conditionality:
·    Those which are
connected to each of the 11 thematic objectives and the related investment
priorities of funds. The identification of the conditionalities which are
applicable in this respect depends on the objectives and priorities that the
programme in question has selected to focus on. They are linked to specific
areas of intervention of the ESI funds and relate to effective policies being
pursued, EU law affecting the implementation of the funds being transposed and
adequate administrative capacity being in place (see Box 1).
·    More general ones
linked to horizontal aspects which apply to all programmes to ensure that
minimum requirements are in place with regard to anti-discrimination, gender
equality, disability, public procurement, state aid and so on.
In case ex-ante conditionalities are not
fulfilled at the stage of programme adoption as assessed by the Member States
themselves and subsequently by the Commission, Members States are required to
prepare action plans demonstrating how the necessary conditions will be put in place
in due time so as not to impede the effective and efficient implementation of
the funds. Failure to carry out the action plan by the end of 2016 could lead
to a suspension of EU payments. Non-fulfilment of critical elements which puts
effective spending at serious risk could already lead to a suspension of EU
funding at the stage of programme adoption by the Commission.

Box : Criteria for fulfilment of ex-ante
conditionality in the area of R&D and innovation

* The European
Strategy Forum on Research Infrastructures is a strategic instrument to develop
the scientific integration of Europe and to strengthen its international
outreach. The competitive and open access to high quality Research
Infrastructures supports and benchmarks the quality of the activities of
European scientists, and attracts the best researchers from around the world. See
http://ec.europa.eu/research/infrastructures/index_en.cfm?pg=esfri

1.4.      Achieving and demonstrating results

In the past, the implementation of Cohesion
policy support has focused in some places more on spending and management than
on performance in terms of reaching specific objectives. Programmes have often
not been sufficiently precise about the objectives they aimed to achieve and
the way in which they would do so, which made it difficult to monitor them and
to evaluate their performance. 
In some cases Member States were reluctant to
set targets or they set targets that that they knew would be easy to achieve
and therefore were not meaningful ones against which outcomes could be
assessed. This in turn has limited the ability of evaluations to measure the
effects of interventions and to understand better which measures were most
effective and why.
Against this background, a greater focus on
results through better indicators, reporting and evaluation is at the core of
the reform of Cohesion Policy. 
The focus on results needs already to be built
in at the stage of designing programmes. The design has to be based on a clear
intervention logic starting with identifying development needs and the changes
the programme is intended to bring about in order to meet these needs and going
on to demonstrate how the spending planned helps to do this. 
Each programme must set ‘specific objectives’
to define the results that are intended to be achieved while taking into
account the needs and characteristics of the area to which it relates.
Programme specific indicators with clear baselines and targets have to be
defined to measure the deliverables which are expected to contribute to the
intended changes. They have to be accompanied by common indicators to be used
by all programmes which will make it possible to aggregate achievements at both
national and EU level.
In order to monitor progress towards achieving
the objectives and targets and in order to promote and reward good performance,
a performance framework needs to be defined for each programme, consisting of
milestones to be attained by 2018, targets established for 2023 and a
performance reserve to be allocated in 2019 if the milestones are achieved. 
The performance reserve amounts to the
equivalent of 6% of national allocations by Member State, fund and category of
region, EUR 20 billion in total. The key challenge for Member States and regions is to identify clear and measurable milestones and targets which are both
realistic and sufficiently ambitious to be meaningful.

Box :
Intervention logic of Cohesion policy in 2014-20 – Example for supporting the
high-tech sector in a more developed region

Description
of specific objective
The
most northern region of Germany, Schleswig-Holstein, wants to increase the
number of knowledge-based and technology-oriented start-ups. The result
indicator in respect of this objective is defined as the average number of
high-tech oriented start-ups relative to every 10,000 people of working age in
the region who are economically active. Measured
in this way, the baseline value in the knowledge-and technology-oriented
sector in the region was 4.45 in 2011[2], which is significantly below the
national average.
Target
for result indicator: The region aims to increase the number of high-tech
oriented start-ups relative to every 10,000 economically active people of
working age to 4.85 by 2023. The ERDF co-financed programme will be one of the ways
of doing this. In addition, there will be a start-up friendly policy pursued by
the region as well as private investment (‘other factors‘). 
Description
of possible action to take             
There
are many different ways a region could support a high level of start-ups in the
high-tech sector. By analysing the weaknesses of the region and from past
evaluations, policy makers concluded that the key problems were obstacles to
funding and knowledge gaps. 
As a
consequence, the region decided to adopt two courses of action: 
 - to
reduce barriers to finance in order to support knowledge sectors and attract
venture capital; 
 - to
support measures for reducing infrastructure barriers to technology as well as incubator
centres.
Appropriate
output indicators for these courses of action are the number of
enterprises receiving support and the amount of private investment which arises
to match public funding. These happen to be included in the list of common
indicators as defined in the ERDF Regulation. In addition, four specific output
indicators will be used in order to assess the number of projects supported,
the number that lead to an enterprise being successfully set up, the number of
knowledge-based and technology-oriented start-ups and the amount of space rented
in technology and incubator centres. 
 Source: Draft of Operational
Programme Schleswig-Holstein, adapted.                

1.5.      Aligning EU investment with the European semester

The new policy framework establishes a close
link between ESI funds and the European semester. Relevant country-specific
recommendations (CSRs), i.e. recommendations relating to structural changes
which it is appropriate to bring about through multi-annual investment and
which fall within the scope of ESI fund support, need to be taken into account
by Member States and regions in the preparation of 2014-20 programmes.
Many CSRs do not directly concern ESI funds
(such as those relating to taxation, fiscal frameworks, public finances related
to pensions or health costs, regulatory reform of social security or internal
market measures). While some of these reforms are indirectly relevant for setting
the right framework conditions for ESI funds, implementing them requires policy
responses other than from EU investment.
However, the 2013 CSRs also contained a
significant number of recommendations which are relevant for the ESI funds.
These include measures for improving research and innovation, increasing SME access
to finance and business start-ups, raising energy efficiency and modernising
energy networks, improving waste and water management, increasing labour market
participation, upgrading education systems and reducing poverty and social exclusion.
Member States
that received Country-Specific Recommendations (CSRs) in 2013 related to energy,
R&D and innovation
 (Sub-)sector CSR || Member State || Number of Member States 
 Energy networks, renewables and energy efficiency || Bulgaria, Czech Republic, Estonia, Spain, Italy, Lithuania, Latvia, Malta, Poland, Slovakia, Germany, Finland || 12 
 R&D and Innovation || Estonia, France, Luxembourg, Netherlands, Poland, Slovakia || 6 
Another important area covered by the 2013 CSRs
concerns public administration, the judiciary and public service provision.
Those issued included a number which specified the need to improve the
effectiveness and efficiency of public administration, to increase the quality
and independence of the judicial system, to combat corruption more effectively
and to ensure the sound implementation of public-procurement legislation and,
in some cases, more than one of these recommendations (all four in the case of
Bulgaria and Greece).
Examples of Country-Specific
Recommendations (CSRs) in 2013 related to quality of public administration and
good governance 
 (Sub-)sector CSR || Member State || Number of Member States 
 Improving the effectiveness and efficiency of the public administration || Bulgaria, Cyprus, Czech Republic, Spain, Greece, Croatia, Italy, Romania, Slovakia || 9 
 Judiciary reform || Bulgaria, Greece, Spain, Hungary, Latvia, Malta, Romania, Slovenia, Slovakia || 9 
 Improve the business environment || Bulgaria, Greece, Spain, Hungary, Italy, Poland, Romania || 7 
 Anti-corruption || Bulgaria, Czech Republic, Greece, Croatia, Hungary, Italy || 6 
 Public procurement || Bulgaria, Greece, Hungary, Croatia || 4 
 Absorption of ESI funds || Bulgaria, Romania, Slovakia || 3 
Since the modernisation of public
administration has become a cornerstone for the successful implementation of
the Europe 2020 Strategy, the new legal framework puts a particular emphasis on
institutional capacity building and administrative reform. The aim is to create
institutions which are stable and predictable in their relations with the
public, but also flexible enough to react to societal challenges, open to
dialogue with the public and able to introduce new policies and provide better services.


1.6.      A strategic approach to Public
Administration reforms

Institutional capacity is not just a technical
matter of training civil servants, it relates to how public authorities
interact with businesses and people and deliver services to them. Good
governance[3]" is both the basis for, and the ultimate objective of,
institutional capacity building, creating trust and
social capital. Countries with a high level of social capital also tend to
perform better economically. 
Context factors are key to the design of a
comprehensive strategic approach to public administration reform. They include
institutional stability, stakeholder involvement, alignment of goals and
effective cooperation between the various parties involved[4].
Building on these factors, the conditions for
success are:
·     the existence of a
customised, country-specific approach that clearly identifies the main
weaknesses of administrations as well as the main policy areas that require
administrative support;
·    sufficient focus on the
regional and local dimension; 
·    the need for the process
of capacity building to follow a framework of coherent reforms as opposed to being
ad hoc[5].
Member States need to adopt a strategic approach
to the modernisation of public administration, as indicated in the Common
Provisions Regulation of the ESI funds, based on ’principles of excellence’[6] (see figure 90).
Figure 1: Principle of excellence

1.7.      Sound economic governance

Investment supported by ESI Funds must take
place in a sound macroeconomic framework for its impact to be maximised. This
is why there needs to be a close link between ESI funding and the economic
governance procedures of the Union. Since both policies have the same ultimate
objective – sustainable, sustained and balanced growth – it is important that
they are closely aligned.
ESI Funds are mainly targeted at public
investment and at tackling the economic and social challenges confronting
Member States. Public investment, however, cannot be effective if public finances
are not sustainable and economic policies are not sound. For instance, when
countries are cut off from financial markets or forced by stringent financing
conditions to introduce difficult economic reforms, it is more difficult when
planning programmes to pursue a long-term investment strategy, to secure the
involvement of the private sector or to ensure an appropriate level of public
investment.
Where national governments fail to put in place
sound economic policies or to carry out necessary structural reforms, it is
likely to reduce the effectiveness of investment supported by the ESI Funds.
Consequently, the new policy framework establishes a direct link between the
implementation of the Funds and respect for EU economic governance -or, more
specifically, action taken at national level to put in place sound fiscal
policies, to respond to changing economic circumstances and to carry out key
structural reforms (‘macroeconomic conditionality’).
In this regard, it should be emphasised that
the economic and fiscal policies carried out at regional level cannot be seen
in isolation from those implemented at national level. The targets set for the
latter at EU level apply to all tiers of government. Ensuring proper
coordination between them is therefore essential to ensure consistency of the overall
fiscal policy stance and equitable burden-sharing between levels of government.
Macroeconomic conditionality, therefore, increases the incentive for all tiers
of government to manage public finances prudently and there is a collective responsibility
to ensure this.
 Box - The link between the macroeconomic framework and the effectiveness of ESI funds Article 175 TFEU requires Member States to conduct their economic policies and coordinate them in such a way as to attain economic, social and territorial cohesion objectives, so establishing a clear link between national economic policies and Cohesion Policy. There are many channels which link the achievement of Cohesion Policy objectives with Member State economic and budgetary policies. First, Cohesion Policy is aimed at fostering growth and development, notably by helping to establish favourable conditions for investment in physical and human capital and technology. Macroeconomic imbalances can jeopardise this by, for example, deterring private investment because of high inflation or high government borrowing. Secondly, according to the principle of additionality, Cohesion Policy is supposed to add resources to those invested by Member States and to complement national efforts in this respect. This implies that governments need to ensure that it is possible to maintain levels of public investment in the areas covered by Cohesion Policy. This can be seriously compromised if the need to reduce budget deficits leads to public investment being reduced. The empirical link between the macroeconomic framework and the effectiveness of ESI funds has been examined in a recent analytical paper[7], which estimates the relationship between macroeconomic policy and indicators of development objectives using standard econometric techniques to show that: (i) sound fiscal policy, and more specifically smaller government deficits and debt levels relative to GDP, contribute to socio-economic development and the achievement of EU objectives in this regard; (ii) higher government current expenditure, including on debt interest, can impede socio-economic development, while public investment (measured in terms of net fixed capital formation) is positively associated with an improvement; (iii) the ESI funds contribute to achieving EU socio-economic objectives; (iv) but their effectiveness is greater when government debt levels and net foreign liabilities are low. These findings provide support for linking ESI funds to economic governance through macroeconomic conditionality. 
The link between EU funding and macroeconomic
governance is not new. It has been acknowledged since the Maastricht Treaty and
has been enshrined in the Cohesion Fund legal framework since its creation.
Moreover, in the Eurozone, new commitments have recently been made in respect
of the Stability and Growth Pact and broadening and reinforcing economic policy
surveillance to cope with the economic crisis (through the adoption of what is
known as the  ‘Six Pack’). 
The objective of the new legal provisions on
macroeconomic conditionality is to ensure, on the one hand, that the
effectiveness of the ESI Funds is not undermined by unsound macroeconomic
policies and, on the other, that the Funds are directed to tackling emerging
economic and social challenges which are long-term and structural in nature
rather than short-term and cyclical. 
Macroeconomic conditionality is designed to be
applied in a gradual and proportionate way. The suspension of ESI funding is
regarded as a last resort when a Member State reaches a significant level of
non-compliance under the various EU economic governance procedures. Any
suspension will be linked to the seriousness of the breach to ensure that it
does not go beyond what is necessary to ensure that funding is used
effectively. 
Macroeconomic conditionality consists of two
strands:
(1) Reprogramming of ESI funds: this concerns amendments to the Partnership Agreements and
programmes during implementation with a view to providing targeted support to
European semester CSRs in order to respond to changing economic realities,
structural reform needs or emerging imbalances or to maximise the impact of the
ESI funds on economic development and competitiveness. Such amendments could,
for example, cover: 
·    support for
labour market reforms that will improve its functioning, for upgrading skills
and lifelong learning and for measures to increase labour market participation;
·    support for
measures to foster competitiveness such as for improving education and training
systems or for R&D and innovation;
·     support for
investment in to infrastructure;
·    support for
measures to meet climate and energy targets and objectives, such as for
reducing greenhouse gas emissions, expanding renewable energy and increasing energy
efficiency to reduce import dependency, lower costs and promote green growth; 
·    support for measures
to improve the management of natural resources and the sustainability of
transport systems;
·    support for
SMEs; 
·     support for
measures to improve the quality of governance such as by improving
administrative capacity and the data collected to monitor, assess and guide
policy.
Failure of a Member State to comply
satisfactorily with a request from the Commission to amend its Partnership
Agreement and relevant programmes could lead to a suspension of part or all of
the ESI payments to the programmes concerned. Suspended payments would be
released without delay once the Member State responded satisfactorily to the
Commission’s request. Member States would be able to continue submitting
payment claims during the suspension period to avoid them losing EU funding due
to the (n+3) de-commitment rule, so long as the suspension is lifted before the
closure of the programme.
 Box EU Budget: commitments vs. payments The EU budget has two concepts of expenditure: ·    commitments which are legal pledges that the EU will provide finance for specific programmes or initiatives, provided that certain conditions are met ·    payments which are cash or bank transfers to the beneficiaries of programmes Appropriations for commitments and payments often differ because multiannual programmes and projects are usually committed in the year they are decided but are paid over a number of years as the programme or project is carried out. Since not all projects are undertaken in practice or fully carried out, appropriations for payment tend to be less than for commitments. 
(2) Non-compliance in the context of the
Union's economic governance procedures: If a Member
State (i) fails to take corrective action in response to a Council recommendation
to eliminate its excessive deficit in the context of an Excessive Deficit
Procedure, (ii) submits two successive insufficient corrective action plans or
fails to take the recommended corrective action in the context of a
Macroeconomic Imbalances Procedure or (iii) fails to comply with the policy
conditionality linked to a macroeconomic adjustment programme, part or all of
the commitments or payments for the programmes concerned will be suspended.
In these cases, the new policy framework gives
precedence to a suspension of commitments rather than a suspension of payments
so as to limit the adverse consequences for recipients of ESI funds while
maintaining an incentive for economic adjustment. ESI payments will only be
suspended when immediate action is sought and in cases of significant
non-compliance. A suspension of commitments, moreover, will only apply to those
for the next financial year. This should not directly affect programme
implementation so long as payments can continue to be made against previous
commitments, which remain open for a period of three years following the year to
which the budget commitment relates. 
During this period the Member State can implement measures to correct its excessive deficit or excessive macroeconomic imbalance
or to implement and comply with its macroeconomic adjustment programme. As soon
as it is established by the Commission that the necessary corrective action has
been taken, the suspension would be lifted and the commitments concerned would
be re-budgeted.
The level of suspension will increase gradually
in line with the seriousness of the breach to ensure a proportionate response
which takes account of the degree and persistence of non-compliance and does
not go beyond what is necessary to ensure the effective use of ESI Funds. Equal
treatment of Member States will also be ensured in line with the provisions set
out in the Common Provisions Regulation.
In particular, the new policy framework
provides for a ’double capping’ method so as to limit the level of suspension
of commitments of ESI funds to (i) a particular proportion of the funds and
(ii) a particular ratio of the GDP of the Member State concerned. This is
considered to be the simplest and fairest approach to ensuring equal treatment
given the large differences in the scale ESI funding in relation to GDP between
Member States. It was also the approach applied in the case of Hungary which was subject to a suspension of Cohesion Fund commitments in 2012.
The specific economic and social circumstances
of Member States will be taken into account when determining possible
suspensions. On the one hand, all economic governance procedures include
derogation or escape clauses that will be activated in the case of exceptional
economic circumstances or events beyond the control of policy-makers.
Consequently, macroeconomic conditionality can only be triggered if these
escape clauses are not fulfilled. 
In addition, the legal framework allows for the
economic and social circumstances of the Member State concerned to be taken
into account when determining the level and scope of a possible suspension in
order to avoid adding an excessive burden on those already enduring difficult
times. Mitigating factors are high levels of unemployment, poverty and social
exclusion as well as a prolonged economic recession. Similarly, programmes which
are considered to be of critical importance for tackling economic and social
problems, such as those relating to the Youth Employment Initiative (YEI),
poverty reduction or financial instruments for SMEs will be excluded from
possible suspension.

Box : Gradual
application of macroeconomic conditionality in case of non-compliance under the
Excessive Deficit Procedure 
(indicated timing is
purely indicative) 

[1]       In addition, a specific allocation of EUR 1.6 billion is
foreseen for the Outermost and northern sparsely populated regions. The
financial allocation for the European Territorial Cooperation goal amounts to
EUR 9.6 billion.
[2]       Derived from an analysis carried out by the Centre for
European Economic Research (ZEW Start-ups panel).
[3]       This can be defined as “the manner in which power is
exercised in the management of a country’s economic and social resources for
development”.
[4]       SEOR, 2006, Evaluation of the ESF support to Capacity Building, Rotterdam, the Netherlands.
[5]
      European Commission, 2005, Strengthening institutional capacity and
efficiency of public administrations and public services in the next
programming period (2007-2013), Working Note. DG Employment and Social
Affairs.
[6]       Principles of Excellence. Source: European Institute of
Public Administration.
[7]       See: Mariana Tomova, Andras Rezessy, Artur Lenkowski,
Emmanuelle Maincent 2013, EU governance and EU funds - testing the
effectiveness of EU funds in a sound macroeconomic framework , Economic
Papers 510, Directorate-General for Economic and Financial Affairs, European
Commission.
http://ec.europa.eu/economy_finance/publications/economic_paper/2013/pdf/ecp510_en.pdf

1.8.      Preserving
growth-enhancing investment

Adequate levels of investment are a
precondition for competitiveness and development. Public investment tends to
increase the rate of return of private capital, boosting economic growth in the
long-run. In times of recession, characterised by sluggish demand, loss of
output relative to potential and low private investment, public investment can
stimulate growth in the short as well as long-run through its effect on demand.
As indicated in Chapter 5, both public and private investment has declined
significantly over the past few years reaching record low levels in some
countries. Tight budget constraints and spending cuts have seriously affected
growth-enhancing expenditure. 
The Commission’s Annual Growth Surveys of 2012
and 2013 recommended maintaining an adequate pace of fiscal consolidation while
preserving investment aimed at achieving the Europe 2020 goals for growth and
jobs. In 2012, the Communication from the Commission, A blueprint for a deep
and genuine economic and monetary union - Launching a European Debate' (COM
(2012) 777 final/2) emphasised that public investment is one of the relevant
factors to be taken into account when assessing the fiscal position of a Member
State, notably when deciding to open an Excessive Deficit Procedure (EDP). It
also proposed that, when assessing Stability and Convergence Programmes,
non-recurrent public investment with a proven impact on the sustainability of
public finances could qualify for a temporary deviation from the medium-term
budget objective or the adjustment path towards it 
Government investment projects co-financed by
the EU Structural and Cohesion Funds (as well as Trans-European-Networks and
Connecting Europe Facility) were considered the natural candidates in this
regard, as they fall into the category of productive spending. They, therefore,
support GDP potential in the medium-term and contribute to increasing
growth-enabling infrastructure, human capital (through training and education),
and total factor productivity (through innovation and institutional reforms).
This proposal is particularly relevant in a context where a number of Member
States report difficulties in continuing to co-finance Cohesion Policy
programmes when they have to meet the fiscal targets under the Stability and
Growth Pact (SGP). 
Accordingly, an ’investment clause’ for Member
States has been included as part of the preventive arm of the Stability and
Growth Pact (SGP), i.e. for Member States which are not in an Excessive Deficit
Procedure (EDP). It constitutes a specific application of Article 5(1) of
Regulation 1466/97 on the surveillance of budgetary positions and the
surveillance and coordination of economic policies of Member States and is
related to the existence of a large negative output gap. It allows Member
States to temporarily deviate from their medium-term budgetary objective (MTO)
or the required adjustment path towards this in specific adverse economic
circumstances and in a context of increasing public investment. The "investment
clause" is implemented in 2013 and 2014. 
In addition to the ‘investment clause’, the SGP
includes several provisions concerning the treatment of government investment.
In the preventive arm of the SGP, investment receives special treatment under
the new expenditure benchmark. In particular, general government gross fixed
capital formation is averaged over a number of years, in order to avoid Member
States being penalised if their investment fluctuates markedly from year to
year. Moreover, all expenditure, including investment spending, on EU
programmes fully matched by EU funding is also excluded from the increases in
government xpenditure under consideration. 
As regards the corrective arm of the SGP, the
specific Protocol on the EDP annexed to the Treaty envisages that budgetary
discipline is assessed against reference values for the general government
deficit and debt which do not differentiate between different kinds of
expenditure. Nevertheless, public investment is one of the relevant factors
that have to be taken into account in the Commission's assessment prior to the
launch of an EDP. In particular, the Commission has "to take into
account whether the government deficit exceeds government investment
expenditure and all other relevant factors". The list of the other
relevant factors includes "developments in primary expenditure, both
current and capital (…) the implementation of policies in the context of the
common growth strategy of the Union, and the overall quality of public finances".

1.9.      Linking additionality verification to the stability and convergence programmes

Additionality is a core principle of Cohesion
Policy intended to ensure that the funding it provides generates added-value.
It means that the EU Structural Funds should complement but not replace
equivalent public expenditure undertaken by Member States. Additionality is
respected if the average national development expenditure in real terms per
year in 2007-2013 is at least equal to the level determined at the beginning of
the period, so that EU funding adds to national investment.
For the 2007-2013 period, verification in the Convergence
regions (including phasing-out regions) in the 20 Member States[1] occurs at three points: 
•   ex-ante when the level of public
expenditure to be maintained (the ‘baseline’) is set;
•   mid-term when the level of actual
expenditure in 2007-10 is determined and the baseline is reviewed;
•   ex-post when the level of actual
expenditure in 2011-2013 is determined and related to the baseline.
The mid-term verification gave rise to three
main findings:[2]
·    The overall level of
national spending on development in the Convergence regions in 2007-10 was 7%
higher than the ex ante level, largely because of an increase in
particular Member States, mainly as a result of government efforts to mitigate
the impact of the crisis or, in some cases, because of the strong economic
expansion before the crisis. 
·    A significant number of
Member States asked for their baselines for 2007-13 to be reduced, mostly
because of fiscal consolidation, though in two cases, it was because of the ex-ante
calculation being corrected. All of these requests were considered to be
justified.
·    Shortcomings were
identified in the method for verifying additionality, which did not produce fully
comparable results across Member States. The ad-hoc process required
considerable resources both for the Member States and the Commission, and it
was not aligned with the review of Member State fiscal plans under EU economic
governance procedures.
As a result, the verification process has been
reformed for the 2014-2020 period, linking it closely with EU economic
governance procedures as well as simplifying it. A single indicator of total
public investment (General Government gross fixed capital formation) has been
chosen to measure the investment effort of national authorities, so enabling
verification to be carried out transparently in the light of the room for
fiscal manoeuvre of each Member State. The reform makes verification simpler,
more comparable and less burdensome. Whereas up until 2007-2013, additionality
was verified in every Member State with a Convergence region, in 2014-2020, it
will be verified only in those where there are significant regional disparities
and where a large proportion of the population live in less developed regions.
This will reduce the number of countries concerned from 20 to 14.[3] 

1.10.    Increasing the role of financial instruments

Financial instruments represent a potentially
resource-efficient way of deploying Cohesion Policy resources by providing
repayable support for investment through loans, guarantees, equity and other
risk-bearing instruments. Besides the obvious advantage of recycling funds over
the long term, they help to reduce the dependence of firms on (non-refundable)
grants and to mobilise additional private co-investment, so increasing the
impact of EU funding. 
Financial instruments have increased markedly
in importance. By the end of 2012, Cohesion Policy support for them amounted to
EUR 12.6 billion in 25 Member States as against only EUR 1.2 billion in
2000-2006. In October 2013, the European Council concluded that programme
negotiations should be used to increase significantly the support from the ESI
Funds for leverage-based financial instruments for SMEs in 2014-2020 and at
least doubling support in countries where access to finance remains tight.
In order to encourage the use of financial
instruments, the new framework increases the extent to which EU funding can be
used to support them. In practice, this means that programme managers have the
possibility of employing financial instruments to pursue all 11 thematic
objectives instead of being limited to three areas as in 2007-2013 (enterprise
support, urban development and energy efficiency).
Standardised, ‘off-the-shelf,’ financial
instruments are also being provided for Member States with less experience of
them, with pre-defined terms and conditions to facilitate rapid roll-out. Some incentives
are available for financial instruments: for contributions from Operational
Programmes to an EU-level financial instrument under Commission management, up
to 100% of the support can come from the ERDF, ESF or Cohesion Fund, and for
funding allocated to national or regional instruments under shared management, the
EU co-financing rate is increased by 10 percentage points if a priority is
fully carried out by such means. 
The Commission and the EIB are jointly setting
up a new risk-sharing instrument which combines financing from ESI Funds,
Horizon 2020 and the COSME programme with EIB loans to generate additional
lending to SMEs (the ’SME Initiative’).
Financial instruments can potentially increase
access to finance for a wide range of organisations and individuals, including
enterprises investing in innovation, households seeking to improve their energy
efficiency and people pursuing their business ideas. They can also help to fund
public infrastructure or other projects that comply with the strategic
objectives of Cohesion Policy and at the same time yield a financial return.
Nevertheless, financial instruments are not
suitable in all circumstances. This is why their use has to be justified on the
basis of an ex ante assessment to identify inter alia the market
failure or sub-optimal investment situation which they are intended to correct
and to verify investment needs and that a critical mass is likely to be
achieved.

1.11.    Reinforcing cooperation across Europe

European Territorial Cooperation (ETC) is one
of the two main goals of Cohesion Policy in the present period, providing a
framework for joint action and policy exchanges between national, regional and
local actors in different Member States. The challenges faced by Member States and regions increasingly cut across national and regional boundaries and
cooperation at an appropriate territorial level is needed to tackle them
effectively. ETC can accordingly contribute to furthering the Treaty objective
of territorial cohesion: 
·    trans-border problems
(such as pollution) can be overcome most effectively by all the regions
concerned cooperating to avoid disproportionate costs for some and free-riding
by others;
·    cooperation provides a
means of sharing good practice and know-how;
·    cooperation can realise
economies of scale and help to achieve a critical mass, such as in relation to
clusters of a particular activity;
·    cooperation can improve
governance through coordination of policy measures and investment which span
national borders;
·    cooperation with EU
neighbouring countries can contribute to safety and stability and establish
mutually beneficial relationships;
·    cooperation between
countries is essential in macro-regions, such as those around the Baltic Sea, to manage eco-systems in support of sustainable growth and employment. 
The new ETC legal framework also envisages
concentration of investment in particular policy areas as well as an increased
focus on results, including the establishment of programme-specific milestones
against which progress can be assessed. It contains new provisions to
facilitate programme implementation, in particular: 
·    strictly defined
selection criteria to ensure that funding is given to genuinely joint
operations; 
·    a reduction in the
number of authorities involved in programme implementation and a clarification
of their respective responsibilities; 
·    simplification of the
rules on eligibility and prior-written confirmation in this regard by all
Member States participating (and, where applicable, third countries) for each
programme to help avoid the legal uncertainties which could arise as it is
carried out.
In the 2007-13 period, at the request of the
European Council, two macro-regional strategies were adopted by the Commission,
one for the Baltic Sea and one for the Danube. Another two, for the
Adriatic-Ionian and Alpine Regions, are under preparation. Each of these covers
several Member States and regions and is aimed at increasing the coherence of
policy and the overall impact of public funding. 
Map
1 Cross-border cooperation
programmes 2014-2020
Map 2: Transnational cooperation programmes
2014-20
 || 

2.     PRELIMINARY
ASSESSMENT OF THE PROGRAMME NEGOTIATIONS 2014-20

The Commission has adopted a proactive
approach in the new period to try to ensure a timely start of programmes. As
early as autumn 2012, the Commission sent position papers to all Member States
outlining its views of the development needs and funding priorities for each of
them. In addition, an informal dialogue took place in 2013 with most Member
States to identify funding priorities at an early stage and accelerate the
adoption of the programming documents as soon as possible in 2014.
At the time it adopted this report, the
Commission had received all 28 Partnership Agreements (PAs) though only just
over 150 of the 400 or so expected Operational Programmes (OPs). Negotiations
with Member States and regions are ongoing. The following, therefore, provides only
a preliminary indication of the extent to which the main elements of the reform
have been incorporated in the new strategies and programmes. 

2.1.      Funding priorities in 2014-20 

Overall, around EUR 336 billion are allocated
to national and regional programmes under the Investment for growth and jobs
goal.[4] The resources are divided as follows: EUR 187.5 billion to the
ERDF, EUR 63 billion to the Cohesion Fund, and EUR 85 billion to the ESF which
is higher than the legally required minimum ESF allocation of EUR 80 billion.[5]
(i) Allocation by thematic objective (TO)
The largest allocation from the three funds is
foreseen for support for transport and energy infrastructure (TO7) (EUR 59.1
billion or 18.2% of the total), followed by strengthening R&D and
innovation (TO1) (EUR 40 billion, 12.3% of the total) and support for a low
carbon economy (TO4) (EUR 37.8 billion, 11.6% of the total). 
Figure 1 : Allocation to thematic objectives (EUR billion
at current prices)
Financial allocations to support employment
(TO8), SMEs (TO3), education and training (TO10), environmental protection
(TO6), and social inclusion measures (TO9) are on much the same scale, around
EUR 32-33 billion (or around 10% of the total), while allocations to support
the digital agenda (ICT; TO2), adaptation to climate change (TO5) and good
governance (TO11)[6] are much smaller (Figures  91 and 92).
Figure 2 : Allocations to thematic objectives (% of
total)
(ii) Allocations to thematic objectives by Fund
The allocation to thematic objectives from each
Fund reflect the provisions of the new regulatory framework, in particular the
priorities on which they are concentrated (see Figures 93 and 94): 
Figure 3 : Allocation to thematic objective by Fund
(EUR billion at current prices)
The ERDF will be used to pursue all 11 thematic
objectives (see Figure 94), but resources are concentrated on support for
R&D and innovation (EUR 40 billion, 22% of the ERDF total), SMEs (EUR 32.7
billion, 18% of the total), a low carbon economy (EUR 30 billion, 16.5% of the
total), and transport and energy infrastructure (EUR 25.6 billion, 14% of the
total).
Support from the Cohesion Fund is concentrated
on four objectives only (i.e. 4-7), just over EUR 33 billion being allocated to
investment in transport and energy infrastructure (54% of the total), EUR 17
billion (27.5% of the total) to environmental protection  and EUR 7.7 billion
(12.5% of the total) to low carbon economy. 
Like the Cohesion Fund, financial support from
the ESF is focused on four objectives, almost EUR 31 billion (38% of the total
available) being allocated to employment, EUR 26.3 billion (32.5% of the total)
to education and training and EUR 20.9 billion (26%) on social inclusion
measures.
Figure 4 :
Allocations to thematic objectives by Fund (% of Fund total)
(iii) Allocations to thematic objectives by
group of countries
The relative allocation of funding to the
different objectives varies significantly between more and less developed
Member States[7], reflecting their different levels of economic development and
investment needs, though there will equally be variations between countries in
each of these categories for the same reasons. 
In the more developed Member States, the share
of investment in R&D, innovation, ICT, SMEs and a low carbon economy (44.5%
of the total) is significantly larger  than in less developed ones (35%). 
The same is true for investment in employment,
social inclusion, education and training and administrative capacity building
(41% of the total in the more developed countries, just under 27% in the less
developed).
Less developed Member States, on the other
hand, have earmarked a larger share for investment in environmental protection
and adaptation to climate change than more developed ones (14 % as against
8.5%). 
The difference is even more pronounced for
transport and energy infrastructure, for which the share is almost 5 times
larger in the less developed Member States than in more developed (24% as
against just under 6%).
Figure 5 : Allocation to thematic objective by
group of countries (% of total)
The situation is of course different in terms
of the absolute amounts allocated to the various objectives because of the much
larger scale of funding going to the less developed countries. Whereas the
share of investment allocated to innovation, ICT, SMEs and a low carbon economy
as well as to employment, social inclusion, education and administrative
capacity building is smaller in less developed Member States than in the more
developed ones, the amount of funding going to these objectives is significantly
larger (Figure 96). It is larger still in relation to the population in these
countries, which is only around a third of that in the more developed ones. 
Figure 6 Allocations
to thematic objectives by group of countries (EUR billion at current prices,
excluding technical assistance)
(iv) Funding priorities 2014-20 as compared
with 2007-13
The new programming period brings a shift of
funding priorities compared with 2007-13 reflecting the close link between Cohesion
Policy and the Europe 2020 strategy.[8]
Around EUR 124 billion is allocated to R&D
and innovation, ICT, SMEs and a low-carbon economy, an increase of almost 22%
compared with 2007-2013. EUR 98 billion is to be invested in employment, social
inclusion and education and training measures, slightly more than in the
previous period, while  almost EUR 4.3 billion is allocated to good governance
(institutional capacity building and the efficiency of public administrations),
72% more than before.
On the other hand, EUR 59 billion is allocated
to transport and energy infrastructure, a reduction of 21% from 2007-2013,
while investment in environmental protection is down by 27%.
In short, Member States and regions will invest
more in the areas identified as ERDF priorities (R&D and innovation, ICT,
SMEs, and a low-carbon economy) and ESF priorities (employment, social
inclusion, education and training and good governance). In turn, less funding will
go to transport and environmental infrastructure.
Figure 7 : Allocations by thematic objective 2014-20
vs. 2007-13 in the EU-28
(% of total)
These changes are common to both less developed
and more developed Member States, though the shift to ERDF and ESF priorities is
more pronounced in the latter as is the reduction in funding for transport and
energy infrastructure.
Figure 8 : Allocations by thematic objective 2014-20
vs. 2007-13 in more developed Member States (% of total)
Figure 9 : Allocations by thematic objective 2014-20
vs. 2007-13 in less developed Member States (% of total) 

2.2.      Aligning
investment with Country Specific Recommendations

Many Country-Specific Recommendations (CSRs)
relate to medium and long term challenges which need to be tackled through a
combination of structural reforms and investment. Several of them are directly
linked to the thematic objectives of the ESI Funds such as the reform of labour
markets, educational systems and public administration, the promotion of
science and innovation, the provision of high quality social and health
services or the upgrade of transport and energy infrastructure.
The Partnership Agreements (PAs) and draft
Operational Programmes (OPs) generally reflect the relevant CSRs by identifying
the related development and investment needs. But only in some cases are the
results expected from the investment supported by the funds clearly related to
the CSRs specified and there is a need for more detail on the way that the CSRs
concerned will be put into effect in the programmes. Some recommendations
clearly require more than one Fund to support the intervention needed and
Member States should ensure that the relevant Funds will do so.
Most Member States and regions have prepared
innovation strategies for smart specialisation to accelerate economic
development and to narrow the knowledge gap. It is important that these
strategies focus on investments which reach a critical mass and best reflect
regional potential. More emphasis needs to be put on ‘soft’ forms of support,
on promoting market-driven research and cooperation with the private sector
instead of funding predominantly research infrastructure and equipment.
Some Member States have brought forward
programmes that establish clear links between the digital economy and
innovation. This is important as investment in high speed broadband and ICT is
needed to overcome particular bottlenecks and to encourage market-driven
solutions. For example, it is essential to focus investment in broadband on
next-generation networks to ensure that less developed regions do not fall
further behind. Coordination between Cohesion Policy, Horizon 2020 and other EU
programmes is also critical as regards smart specialisation strategies at
national and regional level. 
Many Member States consider the strengthening
of the competitiveness of SMEs to be central to their growth strategy and it is
expected that financial instruments will play a major role in this regard.
However, there is limited interest so far in the new SME Initiative. Moreover,
there is a risk of ‘business-as-usual’ support for SMEs regardless of the
sector and the activities in which they are engaged. Support should be tailored
to the needs of enterprises and their growth potential to ensure a large
leverage effect and a quick take-up of funding.
In the PAs of a number of Member States,
energy, climate change and the environment are well integrated into their
economic development strategy. Several have put specific emphasis on energy
efficiency or developing renewable energy as a means of creating new
businesses, jobs and export opportunities, while also reducing greenhouse gas
emissions. However, the link between investment and the expected results in
relation to the climate change objectives needs to be made clearer in some
cases.
Given the challenges of high unemployment and
increasing poverty, the focus on the inclusive growth objectives could be
stronger in some PAs. The Commission is also of the view that the funding
allocated to education is as yet not sufficient to achieve the priorities
identified. In some PAs, low priority is given to active measures for social
inclusion. To ensure better social outcomes and investment that is more
responsive to social change, social policy reform needs to be more taken account
of in programming. 
Moreover, as regards the Youth Employment
Initiative (YEI), relevant information in some PAs and OPs is relatively
general and does not set out how this new initiative will be delivered and if
and how it will support the implementation of Youth Guarantee schemes. In some
programmes, the actions supported by the YEI need to be more focused on
employment creation.
Despite the existence of a CSR on the
integration of the Roma minority, some Member States do not plan to have a
specific priority for marginalised communities, making it more difficult to
assess how much funding will be allocated to this policy area. Some Member
States do not sufficiently address the needs of this target group, while others
need to develop their strategy and intervention logic further.
It is also important to be precise on how
support from the ERDF and ESF will be coordinated, given that there is a need
for an integrated approach by the two funds. This applies, for example, to
education where investment in infrastructure needs to be combined with teaching
and training measures to ensure that the infrastructure is used effectively. 
In 2014-20, some 88 programmes in 16 countries are
multi-fund programmes, combining resources from the ERDF, Cohesion Fund and
ESF. This is expected to encourage a more integrated approach and more
coherence between policies, funding and priorities.
Public administration reform, with the aim of
improving governance, is not another policy area as such. Rather, the quality
of public administration is often key to a region or Member State being able to develop. 
Administrative modernisation and the quality of
justice are recognised as key factors for competitiveness and inclusive growth.
Many Member States are planning measures to strengthen their public
institutions and to improve their capacity to deliver effective policies,
better administrative services, speedier judicial proceedings, increased
transparency and integrity of public bodies and wider participation of the
public in the various phases of policy-making. Yet, in a number of Member
States where a need for reform of public administration has been identified to
support jobs, growth and increased competitiveness, a clear strategy is missing
and objectives are incomplete and unclear. Moreover, in some of these Member
States a clear political commitment to such reform is lacking.

2.3.       Increasing the impact of investment and
delivering results 

Most Member States have made significant
efforts to adopt measures to satisfy ex-ante conditionalities. It is
essential that relevant criteria are met at the start of the programming period
to eliminate potential obstacles to the investment undertaken being as
effective as possible. The process has not been easy and, in many cases, the
Commission will need to agree action plans to ensure full compliance with the
requirements within well-defined deadlines. 
Conditions, which Member States have found
particularly difficult to meet, concern areas where coherent strategies are
important such as in relation to smart specialisation. Difficulties are also
evident in areas where EU Directives need to be implemented (e.g. as regards
energy efficiency or environmental impact assessment) or where EU regulations
need to be applied effectively (e.g. in relation to public procurement).
In some countries substantial efforts are still
needed to tackle bottlenecks relating to administrative capacity. It is of key
importance for the efficient management of EU funding that a clear and stable
institutional and regulatory framework is in place, that skilled and motivated
staff are attracted and retained and that the tools and instruments used are
appropriate for the effective deployment of the funds. 
Setting clear objectives is at the heart of the
orientation of Cohesion Policy towards results and will be the basis against
which its success will be measured. This represents a real step change. Member States and regions, however, have found it difficult to formulate well-defined
specific goals which the policy is aimed at achieving. Many draft programmes
have continued the practice of expressing vague general aims and of listing a
large number of possible actions in order to maintain maximum flexibility in
the selection of projects at a later stage. 
Until the objectives are expressed in an
understandable and clear way, it is difficult to assess whether the
intervention logic of a programme is sound and that there is a reasonable
chance of the funding allocated producing the expected outputs and making the
intended contribution to the pursuit of ultimate policy aims. 
The performance framework is another new
element. This can only be drawn up when the intervention logic of a programme,
its financial structure and outputs for each priority have become clear, i.e.
relatively late in the drafting of each programme. So far only drafts of these
have been received by the Commission. The main challenge when formulating
performance frameworks is to fix quantified targets for the indicators used at
a sufficiently ambitious, but realistic, level – i.e. at a level that can be
achieved if the programme performs as planned.
Partnership Agreements have in most cases been
drafted after reasonable consultation with partners, although in some cases
there are indications that this dialogue has been insufficient. Important
stakeholders were not involved or their comments are not reflected in the
versions of the documents submitted. The Commission will look very carefully at
how Member States have applied the Code of Conduct on Partnership to ensure
genuine participation by stakeholders. 
Last but not least, the new period requires
strong governance and coordination at the national and regional level to ensure
consistency between programmes and support for Europe 2020 and the CSRs as well
as to avoid both overlaps and gaps in expenditure. This is important in view of
the overall increase in the number of regional programmes (for ESF programmes
it is almost 60% compared to 2007-13).

3.                                                                                                            
ESTIMATED IMPACT OF
COHESION POLICY 2014-2020

As indicated in the previous chapter,
estimating the impact of Cohesion Policy investment is difficult, not least
because it affects a wide range of macroeconomic variables, including GDP,
employment, productivity, the budget deficit and the trade balance which are
also affected by a large number of other factors. Interventions have an impact
on demand since programmes generally result in increased public expenditure
though also increased private spending in many cases. They also have an impact
on the supply-side since they add to investment in infrastructure, plant and
equipment and technology as well as human capital – indeed, their central
purpose is to increase development potential through boosting such investment. 
Interventions, in addition, have direct and
indirect effects. For example, transport projects boost demand directly in the
short-term while improving communication links, which should, indirectly, have
a positive effect on the expansion of businesses and so GDP in the longer-term.
At the same time, interventions might increase the demand for labour and
materials which could lead to higher wages and prices, so reducing cost
competitiveness and adversely affecting GDP. 
Equally, as already emphasised, the fact that
economic performance is affected by a wide range of other factors means that
the impact of Cohesion Policy cannot be identified simply by looking at the
data for GDP and other economic variables. To do so, it is necessary to compare
how the economy would have developed in absence of Cohesion Policy with how it
developed in practice. This is why the use of macroeconomic models, which
capture the way that economies function, is needed. (Specifically, they are
used to generate a ‘baseline scenario’ – representing what would have happened
without the policy - which can then be compared with the actual course of the
economy.)
Macroeconomic models enable both the short-term
impact of policy to be estimated and the longer-term effects which take account
of improvements in the supply-side of the economy which continue after the
programming period is over. They also enable the interaction between direct and
indirect effects to be taken into account. 
In the analysis presented below, two models are
used to simulate the expected impact of the 2014-2020 programmes. The first is
the QUEST III model developed and used by the Directorate General for Economic
and Financial Affairs (DG ECFIN)[9].Since this produces results at the national level, it is
supplemented by a second model, RHOMOLO[10], which is designed to estimate the impact of policy at the NUTS 2
regional level.[11] This incorporates several elements borrowed from economic
geography. In particular, it takes a number of spill-over effects into account
to capture the fact that interventions have an impact not only in the region
where they are implemented but also in other regions. Such spill-over effects
arise from trade linkages between regions as well as from the dissemination of
technology. 

Box
–Constructing the simulations

To carry out the simulations, Cohesion Policy interventions are grouped
into five broad categories: 
–   Infrastructure investment, which includes investment in transport,
telecommunications, energy and environmental infrastructure and is treated in
the model as government investment. This is assumed to raise productivity in
the medium-term through output enhancing effects, which are in turn assumed to
decline slowly as the infrastructure ages.
–   Expenditure on human resources, which includes spending on
education and vocational training as well as on other labour market measures.
This is assumed to improve the skills of the work force, though the effects of this
take time to build up and the gains only become apparent in the long-term, but
they are assumed to be significant and persistent. The effects decline in the
longer-run as people retire.
–   Support to R&D, which includes the establishment of networks
and partnerships between businesses and research centres. This is assumed to
reduce the fixed costs of production. It is also assumed that high-skilled
workers are moved from production to R&D which initially reduces the output
of goods and so GDP, but over time increases in productivity are assumed to dominate
which raises output and stimulates investment. While it takes time for these
effects to become apparent, the output gains in the longer-run are assumed to
be significant and to continue to increase.
–   Aid to the private sector, which includes support for SMEs, tourism
and cultural activities. These are modelled as reductions in the fixed costs of
production and have the effect of boosting growth in the short-run when
spending occurs, but they are also assumed to have long-lasting effects on productivity.

–   Technical assistance, which is modelled as government spending. This
is assumed to have no effect on output in the medium- and long-run
(irrespective of any improvement in the governance of policy which results).
The models incorporate both short-term demand effects and longer-term supply
side effects. The former arise during the period when expenditure takes place
when most of the impact comes from the increase in demand, which is assumed to
be partly crowded-out by increases in interest rates, wages and prices. In the
medium and long-run, the productivity
enhancing effects materialise,
so increasing potential output and allowing GDP to grow free of inflationary
pressure. The effect of the interventions, therefore, progressively builds up over
time.
In RHOMOLO, investment in transport, as well as increasing
productivity, is also assumed to reduce transport costs between regions which
facilitates trade in goods and services and hence boosts economic activity. 
It is assumed, in addition, in both models that Cohesion Policy
expenditure is financed by contributions to the EU Budget by Member States which
are proportional to their GDP and that these contributions are in turn financed
through increases in taxes. The positive impact of the interventions on output
and employment is, therefore, partly offset by the negative impact of these.
The two models have been used to simulate the expected impact of
Cohesion Policy programmes for the period 2014-2020. Since most of the new
programmes have yet to be adopted, funds are assumed to be distributed between
the broad investment categories listed above in the same way as in the
2007-2013 programming period, though adjusted to take account of the features
of the new period that are already known, such as the amount of funding
allocated to Member States and categories of region, the concentration of the
ERDF on particular objectives and the minimum shares of the ESF going to
different countries. 
In order to ensure coherence between the
outcomes of the two models, RHOMOLO has been aligned with QUEST so that its
regional estimates are consistent with the QUEST national estimates. 

3.1.      Estimated impact at the national level

The estimates generated by QUEST of the effects
of Cohesion Policy in the 2014-20 period cover all 28 Member States. They
indicate that the investment funded could lead EU GDP to be 0.4% higher compared
with the baseline (i.e. the non-policy scenario) level by the end of the
programming period in 2023 and EU-13 GDP to be 2.6% higher. EU-15 GDP, however,
is estimated to be only 0.2% higher relative to the baseline (Figure 100). 
Figure 10 : Estimated impact of Cohesion Policy on
GDP
Source: QUEST3R&D simulations, % deviations from baseline
GDP.
The estimates for
individual countries include spill over effects from developments in other
countries. Accordingly, they do not only include the effects of the Cohesion
Policy programmes carried out in the country itself but also take explicit
account of the indirect effects of the programmes carried out in other countries
in the form of increased exports to them.
They take account too of the need to finance
Cohesion Policy expenditure, which is assumed to lead to taxes being higher in
all Member States as compared with the situation without Cohesion Policy. These
higher taxes together with the modest Cohesion Policy investment in the EU-15
explain the limited impact in the latter (which is negative in some countries
where the depressing effect of taxes more than outweighs the expansionary
effect of investment) (Figure 100).
Figure 11: Estimated impact of Cohesion Policy
expenditure on GDP in main beneficiary countries, average 2014-2023
Source: QUEST3R&D simulations, % deviations
from baseline GDP.
The estimated impact of Cohesion Policy
programmes on the GDP of the main beneficiary countries vary considerably,
largely reflecting the differing amounts of funding received (Figure 101). The
relationship, however, is not proportionate, reflecting other factors such as
the composition of programmes. For example, the impact of programmes on GDP is
estimated to be largest in Poland, where funding is less than in Hungary where the impact is estimated to be only the fifth largest. Similarly, funding in Croatia is much the same in relation to GDP as in Lithuania but the impact is estimated to be
significantly larger.
Figure 12 - Cohesion Policy
expenditure and impact, average 2014-2023
Source: QUEST3R&D simulations, %
deviations from baseline GDP, DG REGIO Cohesion spending projections and DG
ECFIN Spring 2013 GDP projections.
The results of the simulation also highlight
the fact that the impact is estimated to build up over the years and to
continue after the programme comes to an end. Most of the increase in GDP
during the period, therefore, comes from higher demand, which is assumed to be partly
‘crowded-out’ by increases in interest rates, wages and prices. It is only in
the medium and longer-term that the productivity enhancing effects of Cohesion
Policy materialise, increasing potential output and enabling GDP to grow free
of any inflationary pressure (Figure 102). By 2030, the effect is to increase
GDP in Poland - where the effect is largest – by an estimated 3.6% above what
it otherwise would be in the absence of Cohesion Policy. 
[1]       Belgium, Bulgaria, Czech Republic, Germany, Estonia Greece,
Spain, France, Italy, Latvia, Lithuania, Hungary, Malta, Austria, Poland,
Portugal, Romania, Slovenia, Slovak Republic, and the UK
[2]       See: Communication from the Commission: Results of the
mid-term verification of additionality 2007-2013, COM(2013)104 final.
[3]       The 14 are Bulgaria, Croatia, Czech Republic, Estonia, Greece, Italy, Latvia, Lithuania, Hungary, Poland, Portugal, Romania, Slovenia and Slovakia. 
[4]
      The financial resources for this goal cover the ERDF (excluding support
for European Territorial Cooperation), the ESF and the Cohesion Fund. Resources
allocated to technical assistance are not considered in this analysis.
[5]       The figures mentioned in this section are preliminary (state
of play: 1 June 2014) and may change in the context of the ongoing programme
negotiations between the Commission and Member States. 
[6]       Investments in enhancing institutional capacity of public
authorities and stakeholders and efficient public administration is considered
as good governance.
[7]       For the purpose of this analysis the less developed Member
States are taken as the countries eligible for the Cohesion Fund in 2014-20.
These are Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Slovakia, Poland, Portugal and Romania, and Slovenia. More developed Member States are those countries which are not eligible for
Cohesion Fund support.
[8]       For 2007-13 the categorisation of expenditure by Member State, objective and Operational Programme has been used to compare with 11 thematic
objectives in 2014-20.
[9]       This incorporates the latest techniques in Dynamic Stochastic
General Equilibrium (DSGE) modelling, which is founded on micro-economic
principles of how individuals, enterprises and other organisations are assumed
to behave.
[10]     This has recently been developed jointly by the Joint Research
Centre-Institute for Prospective Technological Studies and DG Regional Policy.
[11]     See: Andries Brandsma, D'Artis Kancs, Philippe Monfort, Alexandra
Rillaers, 2013, Rhomolo – A Dynamic Spatial General Equilibrium Model for
Assessing the Impact of Cohesion Policy, Working Paper N°1/2013, DG
Regional and Urban Policy, European Commisison, http://ec.europa.eu/regional_policy/sources/docgener/work/2013_01_rhomolo.pdf.
Figure 1: Estimated impact of Cohesion Policy expenditure
Source: QUEST3R&D simulations, % deviations from baseline
GDP.
This continuing build-up over time of the
impact of Cohesion Policy is also reflected in the multiplier which indicates
the increase in GDP per Euro spent. For the EU as a whole, it is estimated at
around 1.5 over the 2014-2023 period and up to 3.75 over 2014-2030. This
illustrates the fact that Cohesion Policy not only boosts demand in the
short-run but strengthens the growth potential of economies through supply-side
effects which persist long after the funding has come to an end.
Cohesion Policy not only has a positive impact
on GDP but also boosts employment. In the short-term, this is mainly a result
of the increase in economic activity which the investment it co-finances give
rise to. In the longer-term, the same investment tends to increase labour
productivity and competitiveness through improvements in infrastructure,
methods of production, the structure of industry, the skills of the work force
and so on. This, accordingly, tends to lead to a further expansion of economic
activity and employment and one which is likely to persist long after the
initial expenditure was undertaken.
As in the case of GDP, the impact on employment
is likely to be particularly large in the main beneficiary countries. For
example, simulations suggest that in Poland, employment could be 1% higher than
it would have been without Cohesion Policy funding during the implementation of
programmes and significantly higher than this in the longer-term.

3.2.      Estimated
impact at the regional level

A model like RHOMOLO which takes account of the
spill-over effects of interventions at the regional level is important for
assessing the full effects of Cohesion Policy. Since regions in the EU are
closely interconnected through trade, the movement of workers, flows of capital
and the diffusion of technology, interventions tend to have an impact well
beyond the places in which they are implemented. The inclusion of such
interconnections in the model, however, makes it more complicated to interpret
the results. In order to illustrate how the various mechanisms represented in
RHOMOLO combine to produce their effects, three simulations each focusing on a
particular area of intervention are presented below.

3.2.1.   Investment
in infrastructure

Much of Cohesion Policy funding goes on
investment in infrastructure. For the 2007-2013 period, it accounted for around
49% of the total and it is still expected to be important in the present
period. There are, however, large differences between regions, expenditure
being considerably higher in less developed regions where the need is greatest.
The impact of investment in infrastructure is captured by assuming that it
reduces the cost of transport between regions and increases the accessibility
of those where it takes place (Map 92 shows the estimated impact of co-financed
investment on the accessibility of each NUTS 2 region). This is largely in the
less developed regions.
 Map 1: Impact of interventions in infrastructure on NUTS 2 regions accessibility, 2030 || Map 2: Impact of interventions in infrastructure on NUTS 2 regions GDP, 2030 
 
Improvements in transport infrastructure mean
that regions have better access to EU markets which increases their exports and
GDP. They also mean, however, a reduction in the price of imports, since the
regions concerned are more accessible to producers elsewhere. This increases
the real income of households and reduces the costs of firms producing in the
region, but it is likely to mean a loss in their share of the regional market
which offsets this while benefiting producers in other regions and boosting GDP
there. The impact of investment in transport infrastructure, therefore, is not
confined to the region where it takes place, since the improvements in
accessibility lead to other regions being able to export goods more easily
which boosts their GDP too. All these effects combine to produce a differential
impact on GDP in the different regions across the EU (Map 93). 
The effect of the inter-relationships between
regions can be further illustrated by simulating a symmetrical reduction in the
costs of transport between five Polish regions: Łódzkie, Mazowieckie,
Śląskie, Kujawsko-Pomorskie and Pomorskie resulting from a transport
project which improves the connectivity between them (Map 94) 
Map 3: Short run
and long run impact of a reduction in transport costs
in five Polish regions
The simulation shows that this would have a
positive impact on GDP in almost all regions, though to differing extents. In
the short-run (defined as the 4-year period following the completion of the
project), the capital city region of Mazowieckie benefits most from the
investment, mainly because it is in the centre of the 5 regions concerned and
enjoys the largest increase in accessibility. In the very long-run, however (45
years after the project is completed), the positive impact spills over more to
the other four regions and regions in the rest of the country also gain as a
result of the increased economic activity generated. This underlines the
importance of taking inter-connections between regions into account when
assessing the overall impact of policy intervention. 

3.2.2.   Investment
in human resources

Cohesion policy investment in human capital
through various measures, which accounted for 21% of total funding for the
2007-2013 period, is projected to account for 23% in 2014-2020. To simulate the
effects of this, it is assumed that an increase in expenditure on training of
1% in a region leads to increase in labour productivity of 0.3%, which increases
the region's competitiveness and so its GDP. It is also assumed, however, to increase
the demand for labour (because of the lower unit labour costs from increased
productivity) which in the long run pushes up wages. 
The net effect by 2030 of the investment in
human capital assumed to take place over the period is significantly positive,
especially in most of the Central and Eastern European Member States where it is largest in relation to GDP (Map 95). 
The difference in the impact between regions,
however, also stems from other factors. First, investment in human resources is
assumed to have a larger effect on GDP in regions where the level of
expenditure on education is relatively low. Secondly, regions which have a
larger proportion of economic activity in labour-intensive industries (such as
much of manufacturing in Central and Eastern Europe) benefit more from an
increase in labour productivity. 
Thirdly, investment in human resources, as in
infrastructure, generates regional spill-overs through trade links, so
benefiting regions elsewhere. It is also, however, assumed to increase wages in
the regions where it takes place, so attracting inward movements of workers
from other regions, which in this case are adversely affected by the loss of
the income and spending resulting from the outward movements concerned. 

3.2.3.   Investment
in R&D

Cohesion Policy also funds investment in
R&D, which accounted for around 12% of total funding in 2007-2013 and which
is expected to increase in 2014-2020. In the model, support to RTDI is assumed
to increase total factor productivity which leads to an increase in GDP both
directly and indirectly through a reduction in production costs. The lower
prices which result stimulate demand and accordingly the level of economic
activity. As in the case of other kinds of intervention, the rise in GDP also
benefits other regions through the increased demand for their exports. 
The model, in addition, takes explicit account
of spatial spill-overs effects specific to R&D. The assumption is that the
further away a region is from the technology frontier, the greater the
potential for absorbing and imitating technological advances made elsewhere.
This implies not only that lagging regions catch up with more advanced ones in
terms of technology but also that an increase in R&D has a bigger impact on
factor productivity there.
 Map 4: Impact of interventions in human resources on NUTS 2 regions GDP, yearly average 2014-2023 || Map 5: Impact of interventions in R&D on NUTS 2 regions GDP, yearly average 2014-2023 
The results of the simulation show positive
effects in all regions with very few exceptions, with those in the Czech Republic, Hungary, Poland and Portugal benefiting most. In Poland for instance, the increase
in GDP ranges from 0.5% to 0.8% a year over the period. 
The effect of interventions in R&D is
assumed to build up considerably over time, reflecting the many indirect
effects generated, especially from the boost to private investment and lower
production costs, which mostly materialise in the long run. For example, while
the short-term impact on GDP in the Podkarpackie region of Poland is estimated to be 0.8% a year on average between 2014 and 2023, by 2030, GDP is
estimated to increase by 3.3% above what it otherwise would have been. In Norte
in Portugal, where the estimated short-term impact on GDP is 0.2%, it is
increased to 1.5% by 2030.
In general, the impact is smaller in Transition
regions than in less developed ones both because of the smaller funding
received under Cohesion Policy and the smaller effect on factor productivity
which is assumed since they lag less behind in terms of technology.

3.2.4.   Combined
impact of investment at regional level

RHOMOLO can also be used to estimate the
overall impact of Cohesion Policy funding in 2014-2020. This is largest in the
Central and Eastern European regions over years 2014-2023 (Map 97). In the
Polish regions of Śląskie, Podkarpackie, Małopolskie and
Lubelskie as well as in Észak-Magyarország and Észak-Alföld in Hungary, GDP is estimated to be increased by over 2.5% a year on average over the period.
This mainly reflects the fact that these
regions are the largest recipients of EU funding, but they also lag behind in
terms of infrastructure endowment, which means that the effect of investing in
this tends to be particularly large. Equally,, a given amount of investment in
human resources adds more to total spending on education in these regions than
in more developed Member States and, accordingly, typically has a bigger
effect. In addition, these regions have more employment in labour-intensive
industries which increases the gain from higher labour productivity.
Even though regions in the more developed
Member States receive much less Cohesion Policy funding, the impact is not
negligible in the less developed among them. For example, GDP is estimated to
increase by around 0.5% a year in Andalucía in Spain and Campania in Italy over the 2014-2023 period. 
In the longer-term, the impact on GDP is much
larger in all regions, most especially those in eastern, central and southern Europe, because of the effect of investment support on their productive potential. For
instance, in Śląskie in Poland, GDP is estimated to be increased by
6.1% by 2030 as a result of the higher investment, over 2.5 times more than the
average impact over the period itself (Map 98). 
The long-term impact is also significant in the
more developed regions, where the short-term impact on demand is small but
where the effect on raising productive potential is much larger. The long-term
impact, moreover, comes partly from the increased demand for their exports
stemming from programmes carried out elsewhere, especially in the less
developed regions, which also tends to increase in scale over time along with
the growth of the latter.
These estimates, however, are based on
simulations which incorporate hypothetical assumptions about the composition of
the expenditure financed under Cohesion Policy. They will be updated once all
the new programmes have been adopted and the breakdown between the various
categories of investment has been decided. Nevertheless, they indicate that the
Cohesion Policy funding made available can have a significant impact on regions
across the EU, particularly on the less developed ones. Whether the impact in
practice, however, is as significant as estimated above will depend to a large
extent on programmes being carried out in a timely way and on the funding
involved being deployed as effectively as assumed in the model. 
 Map 6: Impact of the 2014-2020 cohesion policy programmes on NUTS 2 regions GDP, yearly average 2014-2023 || Map 7: Impact of the 2014-2020 cohesion policy programmes on NUTS 2 regions GDP in 2030